Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Karaşan, Ali | Kahraman, Cengiz

Article Type: Research Article

Abstract: Location selection for a freight village is extremely important since it has strong impacts on quality of life such as reduction of traffic congestion, reduction of carbon emission, and effective use of lands. The inclusion of such criteria in a location selection requires the fuzzy sets to be used in the decision making methodology. In this paper, we propose a novel integrated fuzzy decision model for the location selection of freight villages. In this integrated methodology, we use DEMATEL for determining the most effective criteria and their inner and outer dependencies; ANP for weighting the determined criteria; and TOPSIS for …finding the best location alternative. The proposed model is applied to a case study for the city of Istanbul in Turkey. Show more

Keywords: Intuitionistic fuzzy sets, DEMATEL, ANP, TOPSIS, freight village

DOI: 10.3233/JIFS-17169

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2017

Authors: You, Xinshang | Yang, Qing

Article Type: Research Article

Abstract:   A big group decision making problem is investigated, under the intuitionistic fuzzy environment and multiple constrains. Firstly, this paper proposes a distance formula between different intuitionistic fuzzy numbers, to measure their dissimilarity degree. A numerical example is introduced to demonstrate the advantages of the proposed distance measure over the others’ formula. Secondly, an optimizing model is constructed to calculate the criteria’s weight values, making the proposed method suitable for weight unknown problems. Thirdly, clustering idea is introduced to handle big data caused by big decision group. Here, a clustering algorithm is given which could classify the participating people. Meanwhile, …computer experiments is utilized to handle the calculation question with respect to big data. Clustering result is based on many times of evolutions, which are obtained by a computer procedure. To derive final ranking results, an extended TOPSIS method is applied depending on the proposed distance measure and clustering results. In summary, a decision making algorithm is clearly shown in form of flow chart. Finally, an experimental analysis for selecting proper library construction is given to illustrate the efficiency and reasonableness of the proposed method. Show more

Keywords: Big group decision making, Intuitionistic fuzzy number, Clustering analysis, TOPSIS method, public participation

DOI: 10.3233/JIFS-18615

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2018

Authors: Karaaslan, Faruk

Article Type: Research Article

Abstract: In this study, hesitant fuzzy graph (HFG) structure and some concepts related to HFGs such as homomorphism, isomorphism, weak isomorphism and co-weak isomorphism are introduced. Also, operations of Cartesian product, direct product, lexicographical product and strong product between two HFGs are defined and given their examples. Finally, a decision making algorithm and an application of HFGs in decision making are given.

Keywords: Hesitant fuzzy set, hesitant fuzzy graph, product operations, homomorphism, isomorphism, decision making

DOI: 10.3233/JIFS-18865

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Gulistan, Muhammad | Beg, Ismat | Yaqoob, Naveed

Article Type: Research Article

Abstract: There are many different techniques used so for in decision making problems. Some researchers used fuzzy sets, some used soft sets and some used combination of fuzzy sets with soft sets in order to handle the imprecise information. On the other hand, matrices play very important role in handling such problems. Different researchers used fuzzy matrices and fuzzy soft matrices in decision making problems. Some others generalized tools are Molodtsov’s soft sets, presented in 1999, Smarandache’s neutrosophic sets, in 1999, Jun’s cubic sets, in 2012 and Jun’s neutrosophic cubic sets in 2017. Our aim in this paper is to combine …the above mentioned generalized tools and develop a new generalize approach namely neutrosophic cubic soft matrices. We first introduce the idea of Neutrosophic cubic soft aggregation operators with the help of neutrosophic cubic soft sets and then present the notion of neutrosophic cubic soft matrices and at the end, we present a max-min decision making problem using neutrosophic cubic soft matrices. Show more

Keywords: Neutrosophic sets, cubic sets, soft sets, neutrosophic cubic soft sets, neutrosophic cubic soft matrices

DOI: 10.3233/JIFS-181296

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: E, Cheng-Guo | Li, Quan-Lin | Li, Shiyong

Article Type: Research Article

Abstract: In this paper, we employ a cooperative game to study coalition performance of a parallel service system with nonexponential service times, which is comprised of n independent parallel M/E k /1 queues, where the service times of the coalitions are designed as a closed-form framework. For such a queueing cooperative game, we use the Erlang service time distributions to make analysis of various coalitions more feasible, and specifically, it is easy to set up a characteristic function for the coalitions under an Erlang closed-form framework. Once the characteristic function is given in the queueing cooperative game, we …compute the Shapley value, the Owen value and the core whose aim is to suitably provide the cost allocation for the coalitions. Furthermore, we use numerical examples to give useful observation on the cost allocations for the coalitions through the Shapley value, the Owen value and the core. Show more

Keywords: Parallel service system, cooperative game, coalition, Shapley value, Owen value

DOI: 10.3233/JIFS-18101

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Qian, Junbing | Bao, Liping | Pan, Nan | Ji, Chuankun

Article Type: Research Article

Abstract: This paper presents a method to suppress the thrust disturbance for the permanent magnet linear synchronous motor (PMLSM), which is used as an actuator in an active vibration absorber. Because the characteristics of the working transmission structure of the PMLSM are relatively special, the thrust ripple and load disturbance will yield in the operation, and they will directly affect the control accuracy and positioning precision. Simultaneously, the thrust of the PMLSM directly acts on the object, and the thrust disturbance of the PMLSM will appear in the payload of the vibration absorber. Based on the actuator, the Proportional-integral-derivative (PID) control …is investigated, and the transfer function of the actuator is obtained. Then, the thrust disturbance of the PMLSM is theoretical studied by analyzing the current flows through the PMLSM. A new method of trajectory overlay planning is presented, where the original input is divided into two inputs with different amplitudes and they suppress each other. Based on the method, the PID control can restrain the disturbance to achieve a predesigned output. The effectiveness of the proposed method is verified by simulation and experimental results. Show more

Keywords: PMLSM, actuator, thrust disturbance, active vibration absorber, PID control

DOI: 10.3233/JIFS-169893

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Ding, Quanyu | Wang, Ying-Ming

Article Type: Research Article

Abstract: In multi-attribute decision-making problems, vague decision information is well-represented by intuitionistic fuzzy sets. However, many of the scoring functions of existing methods cannot always obtain a ranking for the alternatives. In this paper, a TOPSIS-based decision-making method is proposed for multi-attribute decision-making problems in which the attribute weights are unknown and the decision information is in the form of intuitionistic fuzzy numbers. First, a revised definition of the scoring function is introduced and used to solve the intuitionistic fuzzy entropy, which is then used to objectively determine the attribute weights. Second, intuitionistic fuzzy-weighted geometric operators are used to integrate the …information. The positive and negative ideal solutions of the comprehensive attribute values are determined, and the similarities between each alternative and the positive and negative ideal solutions are calculated. Finally, the alternatives set is ranked by comparing the relative closeness of the alternatives. This proposed method increases the range of applications of the traditional entropy-weighted method. Moreover, it does not require the decision-maker to specify the attribute weights in advance. The results hence tend to be more objective. Examples comparing this method with existing TOPSIS-based methods illustrate its practicality. Show more

Keywords: Score function, fuzzy entropy, TOPSIS

DOI: 10.3233/JIFS-18963

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Khalil, Ahmed Mostafa | Li, Sheng-Gang | You, Fei | Ma, Sheng-Quan

Article Type: Research Article

Abstract:  The aim of this paper is to correct the assertions (3) and (4) of Proposition 3.6 proposed by Alkhazaleh [Journal of Intelligent and Fuzzy Systems 32 (2017) 4311-4318]. Every notions involved are extend to the arbitrary set case in a clear, rigorous, and non-burdensome manner. A counterexample is given to illustrate the flaw of the assertions. Then we introduce two new notions describing ‘subset’ of n -valued refined neutrosophic soft sets (n -VRNSs for short) and ‘equal’ of n -VRNSs, and give some examples and related propositions. Finally, we use these results to remedy the flaw of the assertions, and …to improve the work of Alkhazaleh. Show more

Keywords: Neutrosophic set, soft set, neutrosophic soft set, n-valued refined neutrosophic soft set

DOI: 10.3233/JIFS-18647

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2018

Authors: Zhang, Qinghua | Liu, Kaixuan | Feng, Lin

Article Type: Research Article

Abstract: Rough set theory proposed by professor Pawlak in 1982 is an important tool to solve uncertain problems. In order to make rough sets deal with uncertain problems better, by considering the stringent notions of mathematical equality and inclusion, the definitions of rough equality and rough inclusion were introduced by Pawlak. But the researches of rough equality and rough inclusion are on a certain granularity space. In this paper, some change rules will be given with respect to the relations of rough equality and rough inclusion between two uncertain target sets in multi-granulation spaces, and the similarity degree between two roughly …equal sets is proposed to describe the similarity of two uncertain sets in multi-granulation spaces. In order to describe two uncertain sets which are rough equality by an approximation set at the same time, the definitions of optimistic λ -approximation set and pessimistic λ -approximation set will be defined from the points of optimism and pessimism, and some properties of them are discussed in detail. Show more

Keywords: Rough set, rough equality, rough inclusion, similarity, multi-granulation spaces, approximation set

DOI: 10.3233/JIFS-181221

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Lu, Guang-Qing | Čereška, Audrius | Augustinavičius, Giedrius | Maskeliunas, Rimas | Ragulskis, Minvydas

Article Type: Research Article

Abstract: A novel planar precise positioning stage on the rotating platform for calibration on raster scales of the rotary encoder is proposed in this paper. The monolithic structure is constructed with a flexible element and two ultra-fine adjustment screws. The structure for required motion is designed and optimized by software package of Solid Works Simulation, and then their performances are evaluated using numerical modelling approach. The mathematical model is then verified by resorting to finite element analysis (FEA) and experiment. The established analytical FEA models are helpful for optimizing a reliable architecture and improving performance of the precise positioning system.

Keywords: Positioning stage, flexible element, finite element analysis, simulation

DOI: 10.3233/JIFS-169894

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Liu, Hui | Zhao, Bin

Article Type: Research Article

Abstract: In order to avoid combinatorial rule explosion in fuzzy reasoning, distributive laws related to fuzzy implications and aggregation functions have been widely studied in recent years. In 2017, Qiao and Hu investigated the distributivity equation I (x , O 1 (y , z )) = O 2 (I (x , y ), I (x , z )), when O 1 and O 2 are additively generated overlap functions and I is an unknown function. In this paper, this kind of distributivity equation continues to be studied at the …situation that both O 1 and O 2 are multiplicatively generated overlap functions and I is a continuous function. Unfortunately, there is no continuous solution for this distributivity equation that is fuzzy implication, but a characterization for the case that I is continuous except for the point (0, 0) is given. More importantly, some solutions to the system of functional equations consisting of I (x , O 1 (y , z )) = O 2 (I (x , y ), I (x , z )) and I (x , y ) = I (N (y ), N (x )) are characterized. Finally, considered any other overlap functions, sufficient and necessary conditions, under which the previous distributivity equation holds when O 1 is an idempotent overlap function, O 2 is an Archimedean overlap function and I is an unknown function, are given. Meanwhile, some solutions to the system of functional equations are also presented. Show more

Keywords: Overlap functions, fuzzy implications, distributivity equations, contrapositive symmetry equations

DOI: 10.3233/JIFS-181279

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Wen, Bor-Jiunn | Syu, Kai-Chen | Kao, Chia-Hung

Article Type: Research Article

Abstract: In this study, a four-degree of freedom (4-DOF) robot arm uses an innovative two-dimensional vision sensing method to grip a moving target on a moving platform. This study utilizes forward and inverse kinematics to establish a dynamic model of the 4-DOF robot arm. A computer as a controller and a single charge-coupled device (CCD) calculates the two-dimensional vision sensing method and sends commands to an Arduino Uno microcontroller to drive the robot arm. According to simulation results of transient and steady states in MATLAB SimMechanics, the response of the dynamic proportional-fuzzy controller is better than the response of proportional–integral–derivative controller. …To demonstrate a precise control of the point-contact grip, this study utilizes a ping pong ball as a target on a moving platform. Using the dynamic proportional-fuzzy controller based on the two-dimensional vision sensing method, the 4-DOF robot arm can position, grip, and carry a moving ping pong ball to a designated place in three-dimensional space, which breaks through the previous two-dimensional limitation using a single CCD. This breakthrough can reduce the weight and cost of the robot arm. Therefore, this study aims to utilize the technology to grip moving targets on a moving platform for manpower cost reduction in the industry or agriculture domain in the future. Show more

Keywords: Four-degree of freedom robot arm, two-dimensional vision sensing method, forward and inverse kinematics, dynamic proportional-fuzzy controller, two-dimension limitation using a single CCD

DOI: 10.3233/JIFS-169874

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Kutlu Gündoğdu, Fatma | Kahraman, Cengiz

Article Type: Research Article

Abstract: All the extensions of ordinary fuzzy sets with three dimensional membership functions such as intuitionistic fuzzy sets (IFS), intuitionistic fuzzy sets of second type (IFS2), and neutrosophic fuzzy sets (NFS) aim at defining the judgments of decision makers/ experts with a more detailed description. Introduction of generalized three dimensional spherical fuzzy sets (SFS) including some essential differences from the other fuzzy sets is presented in this paper. The new type of fuzzy sets is based on the spherical fuzzy distances which have been already defined in the literature. Arithmetic operations involving addition, subtraction and multiplication are presented together with their …proofs. Aggregation operators, score and accuracy functions are developed. The multi-criteria decision making method TOPSIS is extended to spherical fuzzy TOPSIS and an illustrative example is presented. Additionally, a comparative analysis with intuitionistic fuzzy TOPSIS (IF-TOPSIS) is given. Show more

Keywords: IFS, IFS2, NFS, spherical fuzzy sets, decision making, TOPSIS, distance measurement, ideal solution

DOI: 10.3233/JIFS-181401

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2018

Authors: Lee, Jae Kang | Kim, Jung Ok

Article Type: Research Article

Abstract: This study reviewed efficient bridge management using UAVs (Unmanned Arial Vehicles) that have much potential for facility maintenance such as the possibility of regular inspection on inaccessible parts of bridges, easy operation regardless of the operators’ specialty, and economic maintenance. For this study, images were obtained from a UAV and a 3D viewer was created with them for the work efficiency of bridge inspectors, so that the inspectors can see and check inaccessible areas regardless of inspector’s location. It compared various existing inspection methods for problems such as cracks, efflorescence and leakage with the UAV inspection method to analyze the …work efficiency as well as sustainable economic benefit. The main purpose of this study was to figure out whether the proposed inspection using the images from the UAV and 3D viewer can replace the existing inspection methods that cannot be performed easily and analyze the economic benefit of the new method. The study result showed that the UAV image-based bridge maintenance and inspection is possible even though it was found inefficient when images of uneven quality were provided depending on operation of the UAV. Therefore, a UAV operation manual that can help generate images of even quality must be produced. Show more

Keywords: UAV photogrammetry, bridge maintenance and inspection, inspection efficiency, 3D viewer

DOI: 10.3233/JIFS-169873

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2018

Authors: Qi, Min | Yang, Zhanpeng | Ren, Wenjuan | Wang, Hongqi

Article Type: Research Article

Abstract: The Lorentzian manifold theory is an important research object in mathematical physics. In this paper, we propose four generalized Lorentzian-like knowledge measures deduced by the Lorentzian inner product for intuitionistic fuzzy sets. Some theorems are given to show the properties of the constructed knowledge measures. Compared with some other knowledge measures, we point out that there exists some counterexamples for some knowledge measures in the frame of the axiom of entropy measure for intuitionistic fuzzy set defined by Szmidt and Kacprzyk. In order to reduce counterexamples, we give some modified orders which extend the definition of the classical order ⪯ …in the axiom. And the numerical experiments show that the modified orders are more general than the order ⪯ in a sense, such as the order ≾ can break the constraint that the two intuitionistic fuzzy sets with the order ⪯ must fall in the either side of the line y = x . It is noteworthy that these binary relations are not strict partially ordered relations, and the problem, constructing a universal partial order, is still open. At the end of the paper some numerical experiments show that the proposed knowledge measures work well on different datasets. Show more

Keywords: Intuitionistic fuzzy set, Lorentzian knowledge measure, order set

DOI: 10.3233/JIFS-18265

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Shieh, Cheng-Shion

Article Type: Research Article

Abstract: In this paper, a hill-climbing method is adopted to control the output of full bridge circuit to achieve desired constant voltage/current output. A novel technology also is presented to control the rising time of the DC converter output. The hardware implementation of this digital control is based on the Field Programmable Gate Array (FPGA) digital chip. The proposed hill-climbing control algorithm can automatically adjust the Pulse Width Modulation (PWM) control parameter to handle the DC converter output approaching desired one. High frequency power supply with DC switching circuit has been paying more attention to its small size, light weight, and …small electromagnetic interference. Digital control has many different control modes than continuous circuit one, and digital control can be updated at any control mode, unlike continuous circuit design cannot be changed once it is completed. That is, the merit of digital control is flexible and programmable which is why the FPGA digital control used in this paper to control the DC switching circuit. We obtain the FPGA execution code by establishing its corresponding Matlab/Simulink simulation model. After meeting simulation test, the Matlab/Simulink model can be directly transformed into Hardware Description Language (HDL) code. This greatly saving the time of writing HDL code which often is a barrier to the electrical engineer. Finally, a high power, 7.2 KW, DC-DC converter experiment is presented to confirm the feasibility of the proposed control method and design procedure. Show more

Keywords: Hill-climbing method, full bridge circuit, FPGA (Field Programmable Gate Array) digital control, PWM (Pulse Width Modulation)

DOI: 10.3233/JIFS-169866

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Sun, You-Gang | Xu, Jun-Qi | Chen, Chen | Lin, Guo-Bin

Article Type: Research Article

Abstract: The magnetic levitation systems of maglev vehicles face the problems of open-loop instability, strong nonlinearity, model uncertainty, and large external disturbances. In order to solve the problems of model uncertainty and exogenous disturbances simultaneously, a T-S fuzzy model of magnetic levitation system with exogenous disturbances and model uncertainties is constructed to obtain an overall control model. A fuzzy H ∞ robust state feedback controller for magnetic levitation systems is designed based on parallel distribution compensation (PDC) design method and the proposed T-S model. The quadratic stability of the closed-loop magnetic levitation system with fuzzy robust control law is …proved. The linear matrix inequality (LMI) is utilized to obtain a controller which can satisfy the H ∞ performance index and the stability of the magnetic levitation system with the proposed control law is proved by Lyapunov method. Both simulation and experimental results are included to demonstrate that the proposed control law can ensure the stable suspension of the vehicle and can restrain the exogenous disturbance effectively. Compared with conventional PID controller, the presented controller can assure faster dynamic response, stronger robustness and smaller overshoot under both exogenous disturbances and model uncertainties. Show more

Keywords: Nonlinear system, fuzzy control, magnetic levitation system, T-S model, robust control

DOI: 10.3233/JIFS-169868

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Zhang, Xiaoqiang | Li, Lin | Le Vine, Scott | Liu, Xiaobo

Article Type: Research Article

Abstract: The market-oriented rail operation planning and pricing are two key issues to enhance the competitiveness and attractiveness of rail sector. A limitation of the state-of-the-art in this area of research is that supply-side (operation planning) and demand-side issues (affected by the pricing) are generally considered separately. The contribution of this paper is to propose a revenue-maximization model that integrates these two dimensions, based on dynamic ticket-pricing, elasticity in passenger demand, and flexible dispatching. The model considers both operating costs directly borne by the rail service operator and costs indirectly incurred by passengers due to the disutility of unproductive travel time …(i.e. the value of time). The strategy to identify the profit-maximizing joint pricing/dispatching strategy is based on Lyapunov optimization. The Lyapunov optimization is applied to obtain a fully distributed and low-complexity multi-slot algorithm only requiring knowledge of the instantaneous system state. We prove the explicit trade-off between the optimization objective and queue backlog. The Guangzhou-Shenzhen railway (Guangdong, China) is employed as the empirical case study, to expose the properties of the proposed model. Show more

Keywords: Rail service planning, dynamic pricing, Lyapunov drift-plus-penalty, queue backlog, revenue management

DOI: 10.3233/JIFS-181701

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Hu, Xiu-lian | Ke, Sheng-Jie

Article Type: Research Article

Abstract: The initial crisis early warning index system of the supply chain quality has been built up according to crisis inducement, documentary research and corporate research. Then we evaluated the feasibility, importance, independence of the index system by using experts scoring methodology. The initial crisis early warning index system has been filtered by fuzzy inference system (FIS) and the final crisis early warning index system has been established.

Keywords: Supply chain quality, crisis early warning, early warning index, crisis inducement

DOI: 10.3233/JIFS-169870

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: Anderson, James | Suh, Wonho | Guin, Angshuman | Hunter, Michael | Rodgers, Michael O.

Article Type: Research Article

Abstract: This paper presents a procedure for assigning multiple Level-of-Service (LOS) ratings to travel time data sets containing multiple (composite) distributions. Different LOS modes within a mixed data set, the travel time data were fitted to multiple gamma-type distributions using an Expectation Maximization (EM) iterative process. The EM process was enhanced with a Monte Carlo style method, wherein the EM process was run 100 times with different random starting values and the best fit according to an R-squared value was taken. The number of underlying distributions was determined by fitting 1 to 5 distributions and using the Akaike Information Criterion to …determine which number of fits maximized the information content of the fitted function. The resulting final posterior probabilities were then used to separate the data into their respective distributions. Reported here are the results of applying this procedure to travel time data collected in the Metro Atlanta area. It is believed that this method can provide enhanced LOS information, especially when the data contain multiple overlapping travel time distributions. This multiple LOS rating method is not intended to replace the current method, instead it is being developed as a supplementary tool to provide more detailed LOS information, for example providing a more detailed view that captures the underlying performance of each subgroup in addition to a single aggregate LOS measure. Show more

Keywords: Travel time distribution, expectation maximization iterative process, Monte Carlo simulation

DOI: 10.3233/JIFS-169872

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Wu, Huan | Zhao, Tingdi | Jiao, Jian | Chen, Zhiwei

Article Type: Research Article

Abstract: With the increasing of system scale and the growing of functional requirements and interactions within and/or among system hierarchies, there are more difficulties for safety engineers to carry out their works. Especially, the research on phased mission system (PMS) with probabilistic common cause failures (PCCFs) is still in the initial stage and has a lot of limitations, because the current researches have not yet considered the dynamic characteristics of PMSs. In this paper, a modular method is proposed as the theoretical basis to construct the components model in the PMS with PCCF. The relationships between common cause events were discussed …and the probabilistic model of CCFs is extended, so that the model can fit for different statistical relations, and a module-based modeling and analysis method using binary decision diagram (BDD) and Markov model were proposed to deal with static and dynamic module in PMS respectively. Moreover, a standardization of description method for modular method using extensible markup language (XML) is given, based on which the system reliability model can be constructed by computer aided. Finally, the proposed method is demonstrated through a case study. Show more

Keywords: Probabilistic common cause failure, phased-mission system, Markov method, XML, standardization, automatic generation of model

DOI: 10.3233/JIFS-169865

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Liu, Yong | Zhou, Ting

Article Type: Research Article

Abstract: Some factors such as expert information, behavior and time influence the decision-making results in dynamic group decision-making. In view of this, from the angle of group negotiation and system coordination, we exploit the Orness measure constraints and Nash bargaining model to establish a novel dynamic group grey target decision method. In this paper, we firstly define concepts of multi-index group measure matrix, stage bull’s-eye matrix and whole bull’s-eye matrix, which consists of the schemes, the objective, the experts, and the time. Then, based on the maximization of decision group satisfaction and the minimization of system coordination deviation, the asymmetric Nash …bargaining model is used to construct a two-step optimization model. Last, the suggested optimization model is used to solve stage bull’s eye matrix. What’s more, we utilize the Orness measure constraints to establish a phase weight nonlinear programming model, and then use it to solve the weight of the stage and determine the entire bull’s-eye matrix. And we utilize the norm to measure the norm distance between group measure matrix and the stage and whole bull’s-eye matrix of the schemes, so that we can give the stage and whole schemes ranking. Finally, the case of emergency group decision making tests the validity and rationality of the proposed method. Show more

Keywords: Bull’s-eye, group negotiation, Orness measure constraint, dynamic, norm distance

DOI: 10.3233/JIFS-181174

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Wu, Chun-Hui | Chen, Ta-Cheng | Hsieh, Yi-Chih | Tsao, Huei-Ling

Article Type: Research Article

Abstract: According to the reports of the World Health Organization, the abnormal total cholesterol is one of the major risk factors for cardiovascular diseases. Supporting this, a number of prospective studies have examined that the risk of cardiac morbidity and mortality is directly associated with the concentration of plasma total cholesterol. Traditional Chinese medicine has been used to treat cardiovascular diseases since it creates milder healing effects and incurs fewer side effects than Western approaches. However, in real world, the traditional Chinese medicine diagnosis using the meridian system is highly complicated in nature so that it is difficult to create a …general model. In our research, a hybrid evolutionary rule mining approach is proposed to assess the total cholesterol data patterns detected from the traditional Chinese medicine meridian energy. Based on the proposed approach, a rule-based decision-making model can be developed with maximum classification accuracy. Through a numerical experiment, the results of this study were compared with the commercial data mining software and the proposed approach is shown to be a promising method for improving prediction accuracy with fewer type II errors. The research outcomes may have benefits to help diagnose and treat cholesterol abnormalities in traditional Chinese medicine clinical therapy. Show more

Keywords: Rule mining, traditional Chinese medicine, total cholesterol, decision-making

DOI: 10.3233/JIFS-169864

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Ke, Hua | Chai, Shiwei | Cheng, Rong

Article Type: Research Article

Abstract: The rapid development of car sharing raises a concerned question: is it a better alternative to car sales? This paper studies a business model selection problem where an automobile manufacturer with uncertain information chooses his strategy from three options: sale only (SO ), car sharing only (CO ), and both sale and car sharing (SC ). A game-theoretic model is built to investigate what are the key factors influencing the introduction of car sharing and how it brings environmental impact. Our results show that both the selling price and car-sharing fee keep invariable regardless of which business model the manufacturer …chooses. CO is a dominated strategy. Besides, SC dominates SO when producing cost is either sufficiently low or high, while the opposite is true for a medium producing cost. In addition, only when producing cost is sufficiently high, a win-win outcome emerges: the introduction of car sharing not only increases the manufacturer’s profit, but also reduces total vehicle quantity, which helps alleviate urban congestion. Finally, our results prove that the increase of uncertainty degree benefits the manufacturer when SC is adopted. Show more

Keywords: Car sharing, game theory, pricing strategy, uncertain information, business model selection

DOI: 10.3233/JIFS-18961

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2018

Authors: Shieh, Cheng-Shion

Article Type: Research Article

Abstract: This study proposes the digital fuzzy control based on Adaptive-Network-based Fuzzy Inference System (ANFIS) to overcome the tracking problem of a DC-AC and DC-DC boost converter and to implement on a digital computer. The proposed method eliminates the trial and error commonly associated with fuzzy systems. In the proposed design scheme, we take the existing continuous controller as training data of the ANFIS such that the proposed digital fuzzy control can replace original continuous one and can keep the original system performance. It is a sense of digital redesign that this paper proposes a new digital control such that the …state trajectories of the sampled-data closed loop systems close to the continuous-time one. An existing boost converter circuit has demonstrated the feasibility of the proposed methodology. Show more

Keywords: Digital fuzzy control, DC-DC regulator converter, DC-AC tracking converter, adaptive-network-based fuzzy inference system (ANFIS), digital redesign

DOI: 10.3233/JIFS-169863

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Petrovsky, Alexey B.

Article Type: Research Article

Abstract: The paper considers new classes of spaces of finite, bounded, measurable multisets with different metrics, pseudometrics, quasimetrics, symmetrics, and some properties of these metrics. We discuss the possibilities to apply new types of metrics for estimating proximity of objects with many numerical and/or verbal attributes. We use the introduced indexes of similarity and dissimilarity of objects represented as multisets in new methods of group multiple criteria decision making.

Keywords: Multiset, space of multisets, metric, pseudometric, quasimetric, symmetric, multi-attribute objects, similarity and dissimilarity of objects, group multiple criteria decision making, group verbal decision analysis

DOI: 10.3233/JIFS-18525

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Hsieh, Wen-Hsiang

Article Type: Research Article

DOI: 10.3233/JIFS-169904

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-1, 2018

Authors: Li, Chengdong | Yan, Bingyang | Tang, Minjia | Yi, Jianqiang | Zhang, Xiqiao

Article Type: Research Article

Abstract: Traffic flow prediction can not only improve the reasonability of the managers’ decision-making and road planning effectively, but also provide helpful suggestions for travelers to avoid traffic congestion. In order to further improve the prediction accuracy of traffic flow, this study presents one data driven hybrid model for short-term traffic flow prediction. This hybrid model firstly extracts the periodicity pattern from the traffic flow data, then, constructs the functionally weighted single-input-rule-modules connected fuzzy inference system (FWSIRM-FIS) for the residual data after removing the periodicity pattern from the original data, and finally, generates the final prediction results through integrating the periodicity …pattern and the output from the FWSIRM-FIS model. The partial autocorrelation function (PACF) method is adopted to determine the optimal inputs for the data driven FWSIRM-FIS model, and the iterative least square method is utilized to train the parameters of the FWSIRM-FIS. Furthermore, three detailed experiments on traffic flow prediction are made, and comprehensive comparisons with three popular artificial intelligence methods are done to verify the effectiveness and advantages of the proposed hybrid model. According to five comparison indices, the proposed hybrid model can achieve the best prediction performance, although with much less fuzzy rules. The error histograms also verify that the proposed hybrid model has the smallest prediction errors comparing to the three comparative methods. The hybrid approach proposed in this study can also be extended to some other applications which have periodicity patterns, e.g. the traveling time estimate and the electricity load forecasting. Show more

Keywords: Traffic flow prediction, fuzzy method, single input rule module, least square learning, traffic-flow pattern

DOI: 10.3233/JIFS-18883

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Hou, Jinhui | Zeng, Huanqiang | Cai, Lei | Zhu, Jianqing | Chen, Jing | Cai, Canhui

Article Type: Research Article

Abstract: Handwritten numeral recognition is a challenging problem in the character recognition field due to the large variation in the writing styles of different persons and high similarity in the contour of different numerals. To address this problem, an effective multi-task learning network (MTLN) for handwritten numeral recognition is presented in this paper. Based on the observation that the writing style could play an effective complementary role to the learned feature extracted from numerals, the proposed MTLN simultaneously performs the handwritten numeral learning module and the writing style learning module. Consequently, the determination of scratchy/non-scratchy in the writing style learning …module can effectively assist the handwritten numeral learning module to obtain a more robust and distinguishable feature so as to improve the recognition performance. Extensive experiments on multiple existing handwritten numeral datasets have demonstrated that the proposed MTLN can effectively improve the recognition accuracy, and outperform multiple state-of-the-art methods. Show more

Keywords: Handwritten numeral recognition, multi-task learning network, convolutional neural network

DOI: 10.3233/JIFS-169862

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: You, Peng-Sheng | Hsieh, Yi-Chih

Article Type: Research Article

Abstract: Bicycle-sharing systems are commonly established at geographically dispersed locations to create their rental service networks. To provide customers with flexibility and convenience, bicycle-sharing systems commonly allow them to pick up bicycles from one station and return them to a different one. However, allowing customers to return their rented bicycles to different stations can possibly lead to an imbalance in the bicycle rental network. One of the approaches to overcome the bicycle imbalance problem is to apply dynamic pricing to motivate consumers to return the rented bicycles to stations without a sufficient number of bicycles. This study developed a constrained dynamic …pricing model to address the bicycle imbalance problem. Moreover, this study aimed to maximize the total revenues over a planning horizon through dynamic pricing strategies. We identify some necessary conditions for optimal sale prices. Using these conditions, we develop a heuristic algorithm based on linear programming and an evolutionary algorithm to efficiently produce comprise solutions. The proposed model and solution procedure were applied to analyze the bicycle system in Taiwan. Sensitivity analyses were also conducted to investigate the effects of various system parameters. Show more

Keywords: Bicycle sharing, rental network, imbalance, dynamic pricing, algorithm

DOI: 10.3233/JIFS-169899

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Khorrami, Niyaz | Shamloo, Ali Salimi | Parsa Moghaddam, Behrouz

Article Type: Research Article

Abstract: In this paper, Nystrom method was used to solve the Fredholm integral equations of the second kind under interval data. The interval analysis is first presented along with integral equations of the second kind and then Nystrom method is used to find solution of integral equations in the intervals instead of nodes. Also the existence of solution and error analysis is presented. Numerical examples show that the method is efficient and demonstrate a good accuracy.

Keywords: intervals, Interval computations, Fredholm integral equation of the second kind, Nystrom method under interval data.

DOI: 10.3233/JIFS-181206

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Wen, Ta-Chun | Chang, Kuei-Hu | Lai, Hsin-Hung

Article Type: Research Article

Abstract: Personnel selection issues can be viewed as a complicated multicriteria decision-making (MCDM) problem. Choosing the most appropriate personnel directly influences an organization’s competitiveness and its sustainable development. Thus, the personnel selection problem is a critical issue for an organization’s success. However, such dilemmas involve quantitative and qualitative factors. Moreover, deciding on how to allocate limited resources toward cultivating talent increases the difficulty of personnel selection problems. This issue can not be solved effectively by arithmetic average-based methods. To address these issues, this paper combines the minimal variance order weighted averaging (OWA) operator and importance-performance analysis (IPA) to improve personnel selection. …The advantages of the proposed method can deal with quantity and qualitative factors simultaneously in the process of personnel selection, consider the ordered weights between assessment attributes, and establish an IPA grid to provide the reference for decision-making by the management. Finally, an empirical case study of selection of higher-education students is applied to illustrate our method. Compared with the arithmetic average and interval 2-tuple linguistic VIKOR methods, our results indicated that the proposed method generates a more accurate and reasonable ranking of personnel. Show more

Keywords: Decision analysis, human resource management, 2-tuple linguistic representation model, minimal variance OWA, importance performance analysis

DOI: 10.3233/JIFS-171686

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Zhang, Xuefeng | Su, Jiafu

Article Type: Research Article

Abstract: Solution selection plays an important role in crowdsourcing and is an imperative work for requesters. However, to the best of our knowledge, there is few studies focus on the problem of solution selection, especially in crowdsourcing contests for innovative tasks. This paper aims to develop a methodology incorporating quality function deployment (QFD) with 2-tuple linguistic method to assist requesters to select the right solution from a large pool of potential solutions efficiently. The methodology includes three phases. The first phase, i.e. pre-selection, is to screen potential solutions by employing the rule of non-compensatory. The second phase is to construct …relationships between requester’s requirements and solution features using quality function deployment (QFD), and further to determine the weights of solution features using 2-tuple linguistic weighted average operator and fuzzy weighted average method. The last phase is to evaluate the performance of potential solutions with respect to solution features, and further estimate their overall performance. Finally, an illustrative application case on the crowdsourcing platform-Taskcn is presented to demonstrate the implementation and effectiveness of the proposed approach. Show more

Keywords: Crowdsourcing contests, innovative tasks, solution selection, quality function deployment, 2-tuple linguistic method

DOI: 10.3233/JIFS-181122

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Mahapatra, Tanmoy | Pal, Madhumangal

Article Type: Research Article

Abstract: In this article, a new idea of fuzzy coloring of m -polar fuzzy graph is presented while establishing the relationship between chromatic number of m -polar fuzzy graph and it’s underlying crisp graph. Some properties of m -polar fuzzy graph and new concepts of independently strong edge and independently weak edge in m -polar fuzzy graph are proved. The differences between fuzzy coloring of fuzzy graph and m -polar fuzzy graph are discussed. It is also shown that a m -polar fuzzy graph can be decomposed into m fuzzy graphs. Again, from m isomorphic fuzzy graph one …can construct a m -polar fuzzy graph. A relation among chromatic numbers of m -polar fuzzy graph and m such graphs is established. Lastly a real life application of the fuzzy coloring is discussed. Show more

Keywords: m-polar fuzzy graph, α-strength cut graphs, independently weak edges, independently strong edges, chromatic number

DOI: 10.3233/JIFS-181262

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Ashraf, Shahzaib | Abdullah, Saleem | Mahmood, Tahir | Ghani, Fazal | Mahmood, Tariq

Article Type: Research Article

Abstract: The key objective of the present proposed work in this paper is introduced a new version of picture fuzzy set so called spherical fuzzy sets (SFS). spherical fuzzy set is a new extension of picture fuzzy sets and Pythagorean fuzzy sets. In spherical fuzzy sets, membership degrees are gratifying the condition 0 ⩽ P 2 (x ) + I 2 (x ) + N 2 (x ) ⩽1 instead of 0 ⩽ P (x ) + I (x ) + N (x ) ⩽1 as is in picture fuzzy sets. In …this paper, we investigate the basic operations of spherical fuzzy sets and discuss some related results. We extend operational laws to aggregation operators and introduce weighted averaging and weighted geometric aggregation operators based on spherical fuzzy number’s. Further a multi attribute decision making method is developed and these aggregation operators are utilized. Finally, we constructed a numerical approach for implementation of proposed technique. Show more

Keywords: Spherical fuzzy sets, aggregation operators, multi-attribute decision making problem

DOI: 10.3233/JIFS-172009

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2018

Authors: Hu, Ming-Sen

Article Type: Research Article

Abstract: The chemical compound NOx is one of the biggest sources of air pollution, and presently Selective Catalytic Reduction (SCR) is the most frequently used method to dispose of NOx. A proportion of NH3 as a reducer is injected into the system and mixed with the NOx waste gas so as to be treated thoroughly. With sufficient O2 , NOx is reduced to innocuous N2 and H2 O by the catalytic reduction of the catalyst. The purpose of this study is to develop a monitoring system for blending the mixing ratio and concentration of NO automatically and for SCR …catalyst De-NOx performance test analysis. This monitoring system enables the user to set various control parameters and instrument parameters, executes user calibration operations (e.g. zero calibration, full scale calibration and low concentration calibration), and tests the De-NOx performance of the plate type catalyst. In the catalyst De-NOx performance testing process, the system prepares the NO mixing ratio and concentration automatically according to the blending concentration and temperature control curves set by the user and then implements the catalyst bed multi-stage temperature control, so as to complete NO or NH3 concentration detection and automatic data logging as the base of De-NOx performance test analysis. Show more

Keywords: Nitrogen oxides, selective catalytic reduction, De-NOx performance, automatic control system

DOI: 10.3233/JIFS-169896

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Konwar, Nabanita | Davvaz, Bijan | Debnath, Pradip

Article Type: Research Article

Abstract: In this paper we study approximation properties (APs) and bounded approximation properties (BAPs) in the setting of intuitionistic fuzzy n -Banach spaces (IFnBSs). Further, we define strong intuitionistic fuzzy n -continuous and strong intuitionistic fuzzy n -bounded operators and using them we prove the existence of an IFnBS with AP. In addition, we provide examples which show that there exist IFnBSs with the AP which fail to have the BAP.

Keywords: Intuitionistic fuzzy n-Banach space; approximation property, bounded approximation property.

DOI: 10.3233/JIFS-181094

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Luo, Yung-Chang | Chen, Yu-Hsiang

Article Type: Research Article

Abstract: In this study an adaptive on-line speed estimation approach has been proposed for a sensor-less indirect air-gap field orientation controlled (AGFOC) induction motor (IM) drive. The indirect AGFOC IM drive was established by utilizing the stator current and air-gap flux. The estimated synchronous speed was derived from the developed reactive power based adaptive air-gap flux estimator, and the estimation of rotor speed was made by subtracting the slip speed from the estimated synchronous speed. Speed estimation and control by the AGFOC IM drive could be extended to include constant power operation mode by utilizing the field weakening technique. The MATLAB® …∖Simulink ® toolbox was used to simulate this system and all the control algorithms were realized using a TI DSP 6713-and-F2812 card to generate pulse width modulation (PWM) signals to the power stage, actuate an IM to validate this approach (sensor-less AGFOC). Both simulation and experimental responses confirmed the effectiveness of the proposed system. Show more

Keywords: Speed estimation, air-gap field orientation controlled (AGFOC), adaptive air-gap flux estimator, field weakening technique

DOI: 10.3233/JIFS-169895

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2018

Authors: Kuo, Wen-Chung | Wang, Chun-Cheng | Kuo, Shao-Hung | Wuu, Lih-Chyau

Article Type: Research Article

Abstract: Traditional digital image authentication is usually based on signature or fragile watermarks. This performs authentication without any secret hidden data. Until now, many image authentication schemes with error detection based on watermarks or signatures have been proposed. Tampering attack can be detected but the areas tampered with cannot be determined for these schemes. In order to improve this shortcoming, a verifiable data hiding scheme is proposed for digital images in this paper. The main idea of the proposed scheme is combining multi-bit encoding function and multi-group data hiding scheme to increase embedding capacity and strengthen security with parity check to …verify the tampering of digital images having embedded secret messages. Therefore, there are three major contributions in our proposed scheme. First, it can achieve image tamper detection and find what has been modified. Second, it resists collage attack. Third, it can increase the embedding capacity. These contributions are discussed according to experimental results. The proposed scheme includes a high security to reduce detection of hidden data and the MSE analysis also proves this scheme has good image quality. Show more

Keywords: Multi-bit encoding function, parity check, watermark, tamper detection, MSE analysis

DOI: 10.3233/JIFS-169902

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Dai, Jhen-Tang | Juang, Jih-Gau

Article Type: Research Article

Abstract: The purpose of this study is to integrate fuzzy sliding mode control (FSMC) into automatic landing system (ALS) to enhance aircraft safety during landing. FSMC can provide compensation signal to PID controller. The adaptive weight particle swarm optimization (AWPSO) and grey-based particle swarm optimization (GPSO) are applied to tune the matrix of controller parameters of the sliding surface. Fuzzy rules are applied to sliding mode controller to find the gain of the differential sliding function, sliding condition can be satisfied and stable control system can be achieved. PID controller is the main controller of the aircraft and it is also …used for the FSMC controller in learning process. In this study, the proposed intelligent system can improve the ALS to against the wind disturbance and control aircraft landing in severe condition. Stability analysis is provided in the controller design by the use of Lyapunov theory. Show more

Keywords: Fuzzy sliding mode control, particle swarm optimization, automatic landing, wind disturbance

DOI: 10.3233/JIFS-169900

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Hua, Xiujuan

Article Type: Research Article

Abstract: In this paper, L -fuzzy rough sets as a further generalization of the notion of fuzzy rough sets are proposed. Moreover, some properties in lattice ordered effect algebra are presented. A group of approximation operators are defined by the new operation in effect algebra, which is introduced by Zhou X.N., Li Q.G. and Wang G.J. And some equivalent statements in an L -fuzzy approximation space are investigated. Finally, the notion of generalized L -fuzzy relational morphism of lattice effect algebra is introduced and the fundamental properties of it are studied.

Keywords: Effect algebra, Lower approximation, Upper approximation, L-fuzzy rough set, L-fuzzy relational morphism

DOI: 10.3233/JIFS-171920

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: Mao, Wei-Lung | Suprapto,

Article Type: Research Article

Abstract: Nonlinear time series analysis and forecasting are an essential part in a diverse range of physical and natural applications. This paper presents a time-division cerebellar model articulation controller (TDCMAC) network using a modified biogeography-based optimization (modified BBO) learning algorithm for nonlinear time series and measurement data prediction. The TDCMAC method is a time windowing strategy constructed using the CMAC network. BBO algorithm is designed related to the geographical distribution of species over time and space. This study presents two modified migration functions of the essential BBO, i.e. quadratic migration BBO (QBBO) and sinusoidal migration BBO (SBBO) methods, to improve …convergence rate and quality of solution. Five nonlinear time series, including Mackey-glass, Lorenz, Rossler, Limber Pine, and Ponderosa Pine data series, are employed to investigate the proposed predictor. The TDCMAC networks using QBBO and SBBO learning algorithms are compared with the gradient descent (GD) method and other existing heuristic learning methods, including particle swarm optimization (PSO), genetic algorithm (GA), and conventional BBO methods, to verify the estimation performance of the proposed method. The performances are evaluated through an extensive simulation by computing the root mean square error (RMSE), mean absolute percentage error (MAPE), and average relative variance (ARV) metrics. Experimental results demonstrate that the proposed predictor indeed achieve more accurate performances and faster learning speed for time series prediction applications. Show more

Keywords: Time-division cerebellar model articulation controller (TDCMAC), Modified biogeography-based optimization, Nonlinear time series prediction, Mackey Glass time series, Lorenz time series, Rossler time series

DOI: 10.3233/JIFS-171120

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2018

Authors: Kumar, Mohit

Article Type: Research Article

Abstract: The correlation between the performance of attributes and the overall satisfaction perceived by the customers is a successful indirect approach to evaluate the importance of the attributes in services. Recently, the fuzzy importance of attributes was discussed as the fuzzy correlation between the performance of attributes and the overall satisfaction. In this paper, the concept of fuzzy set is extended to the idea of intuitionistic fuzzy set and a novel simple approach is presented to evaluate the importance of attributes as the intuitionistic fuzzy correlation between the performance of attributes and the overall satisfaction. The qualitative input data such …as customer’s opinions are available and expressed as linguistic terms. Each of these linguistic terms is mathematically represented by membership and non-membership functions of intuitionistic fuzzy number instead of a fuzzy number or a crisp number. The calculation is based on the weakest triangular norm (t-norm) arithmetic operations on triangular intuitionistic fuzzy numbers. The proposed approach has been applied to a survey with respect to the quality of hotel services in Oradea (Romania) and then compared with other existing approaches to calculating the importance of hotel quality attribute. Show more

Keywords: Correlation coefficient, intuitionistic fuzzy number, weakest t-norm arithmetic, triangular intuitionistic fuzzy number, intuitionistic fuzzy importance

DOI: 10.3233/JIFS-18485

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Dian, Songyi | Liang, Weibo | Zhao, Tao

Article Type: Research Article

Abstract: Finite-time stability and stabilization problems for a class of interval type-2 (IT2) fuzzy time-delay systems are studied. In this paper, we extend the concept of finite-time stability to IT2 fuzzy time-delay systems. Based on the Lyapunov stability method, integral inequality and some advanced matrix inequalities, a sufficient condition is proposed to guarantee finite-time stability of IT2 fuzzy time-delay systems. Then, by virtue of the results on finite-time stability and Finsler’s lemma, we propose an IT2 fuzzy state feedback controller which can guarantee the closed-loop system is finite time stable. The problem of finite time stabilization can be solved with con …complementarity linearization iterative algorithm. Finally, two numerical examples are provided to verify the effectiveness of the proposed approach. Show more

Keywords: IT2 fuzzy systems, state feedback control, finite-time, time-delay

DOI: 10.3233/JIFS-18933

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Chou, Hsi-Chiang

Article Type: Research Article

Abstract: The rapid rates of industrialization and urbanization have induced considerable changes in family structures, increasing the number of older adults who voluntarily or involuntarily live alone. The rapid increase in the population of older adults living alone has raised many safety concerns, with fall-induced injuries and dementia presenting immediate dangers to older adults. Falls are prevalent in older adults, and not only cause injuries for the individuals, but also impose an extremely heavy burden on family members and caregivers. Furthermore, dementia is common among older adults in aging societies and is usually accompanied by dysfunctions in daily living activities, causing …considerable difficulties for family members. The objective of this study was to develop a remote monitoring and control (M&C) smart floor system for detecting falls and wandering patterns in older adults with dementia in order to provide comprehensive care assistance. The proposed system integrates a floor detection sensor and Wi-Fi technology to analyze and determine the occurrence of falls and wandering in older adults with dementia. Conventionally, detection processes for falls and wandering in older adults with dementia are conducted using visual monitoring or wearable detectors, which may reduce the privacy, comfort, and convenience of older adults. By contrast, the proposed system maintains users’ privacy and eliminates the inconvenience associated with wearing detectors. The system determines fall behaviors and wandering patterns in older adults with dementia; when an accident occurs, the system can issue a warning and notify medical care units or relatives for immediate attention, thus reducing the occurrence of further accidents. The remote M&C and warning functions of the proposed system were verified through experiments. Show more

Keywords: Fall detection, dementia, wandering patterns

DOI: 10.3233/JIFS-169903

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2018

Authors: Weng, Jian-Fu | Su, Kuo-Lan

Article Type: Research Article

Abstract: Automated guided vehicle is the most important research issues for mobile robot development. The important research issue of the automated guided vehicle (AGV) is navigation system in recent years. Navigation system can be divided into self-localization, path planning and obstacle avoidance for indoor service execution. The application fields have security patrol or package delivery. Furthermore, recharging is necessary before the battery power has exhausted. The paper develops the automated guided vehicle that is designed and built with a 4WD mecanum wheel platform. Due to the laser ranger’s high precision, we applied the laser range finder to achieve the environment map …construction, so the self-localization via particles filter (PF) and the path planning algorithms can be utilized with the map. The practical motion and safety avoidance strategies are also proposed for robot motion control. Finally, the sensory fusion methods are also integrated with the laser ranger and RGB-D camera for automated guided vehicle while performing the docking process. The experimental results show the successful demonstrations of autonomous patrol and docking for self-recharging. Show more

DOI: 10.3233/JIFS-169897

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Wang, Zhen | Jin, LeSheng | Yager, Ronald R. | Mesiar, Radko | Kalina, Martin | Špirková, Jana | Borkotokey, Surajit

Article Type: Research Article

Abstract: We study the Yager OWS aggregation and the Irregular normalized Yager OWA aggregation under infinite environment. Two evaluation problems are proposed to motivate their applications. Few distinguishing properties are discussed. We show that such aggregations use the same type of weights, infinite weights (sequence), to embody the involved preferences. Their respective applications in the fields of Scientometrics and Gradual Confidence Aggregation are proposed and analyzed.

Keywords: Aggregation function, Decision making, evaluation, Infinite Ordered Weighted Sum, OWA operators

DOI: 10.3233/JIFS-181291

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2018

Authors: Xu, Bingyuan | Zhou, Zhiheng | Chen, Xi | Yang, Yi | Yang, Zhiwei

Article Type: Research Article

Abstract: A new algorithm for static hand gesture recognition is proposed in this paper, which mainly includes the following four steps: hand segmentation, arm removal, feature extraction and gesture recognition. Firstly, the hand is extracted from the background by using skin-color features and geometric characteristics. Secondly, a new arm removal algorithm is proposed, which can effectively and quickly remove the arm area by using distance transformation operations, and gesture composed of palm and fingers can be obtained. Finally, Hu moments of the gesture image and the number of fingertips are calculated and entered into the Support Vector Machine (SVM) for …training. Experiments have been performed to demonstrate that the proposed algorithm is robust in complex background, and can detect and recognize gestures in real time with an accuracy of 94.89%. Show more

Keywords: Arm removal, static hand gesture recognition, distance transformation, SVM

DOI: 10.3233/JIFS-18681

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Chen, Ta-Cheng | Wang, Sheng-Chuan | Wu, Chun-Hui | Huang, Ke-Wei

Article Type: Research Article

Abstract: This study is to investigate the nonlinearly constrained various signal detector location allocation problems in which the types of detectors and the corresponding numbers and locations can be determined at the same time so as to minimize the maximum detecting failure rate in a specified area. In other words, the objective of the detector location allocation problem is to minimize the maximum failure rate by determining the best possible conjunction of three types of decision variables, i.e. , the type of detector, the numbers of each detector type and where to build up each of them with a limited …resources. So, the quality of reliability of event detecting can be assured and consistent. By the way, the signal intensity usually disintegrates proportionally to some power of the distance from the detector. That makes the longer distance far away the detector, the bigger failure rate in detection of the event. The signal detector allocation problem is described as a mixed-integer nonlinear programming model, usually using math programming or heuristic optimization methods for finding the optimal solution or near optimal solution. While using the both methods, the difficulties encountered are the amount of decision variables and the difficulty of not violating the constraints. In this study, a two-phase evolutionary computation approach based on the immune algorithm and particle swarm optimization has been developed for overcoming the difficulties and finding the optimal solutions for the detector allocation problems effectively. Finally, the performance of the proposed methodology has been evaluated with the commercial optimization software. Numerical results illustrate that our approach is with well performance for the constrained detector allocation problems considered in this paper. As reported, solutions acquired by using our approach are as well as or better than those found by using LINGO® . Show more

Keywords: Location allocation, mixed-integer nonlinear programming, evolutionary approach

DOI: 10.3233/JIFS-169901

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Ünver, Mehmet | Özçelik, Gökhan | Olgun, Murat

Article Type: Research Article

Abstract: The main goal of the present paper is to study the general structure and theoretical properties of a particular type of a fuzzy measure that can be used to model multi criteria decision making problems in which there exist some sub criteria. After constructing the general form of the non-additive set function, we deal with the interaction coefficient, Möbius representation and dual measure related to proposed measure. Finally, we are concerned with the usage of this type of fuzzy measures in multi criteria decision making problems in which at least one of the criteria contains some sub-criteria.

Keywords: Fuzzy measure, nonadditive measure, sub-criteria, multicriteria decision making, Möbius representation

DOI: 10.3233/JIFS-18396

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: Jin, Feifei | Ni, Zhiwei | Chen, Huayou | Langari, Reza | Zhu, Xuhui | Yuan, Hongjun

Article Type: Research Article

Abstract:  The single-valued neutrosophic sets (SVNSs) are useful tools to describe uncertainty and inconsistent information that exist in real world. For SVNSs theory, two important topics are single-valued neutrosophic entropy and single-valued neutrosophic similarity measurer. This paper investigates a multi-attribute decision-making (MADM) method by using single-valued neutrosophic entropy and similarity measure. First, the concepts of single-valued neutrosophic entropy and similarity measure are presented. Then, based on the trigonometric functions (i.e., sine function and cosine function), we introduce two information measure formulas and prove that they satisfy the requirements of the single-valued neutrosophic entropy and similarity measure, respectively. Furthermore, we study the …inter-relationship between single-valued neutrosophic entropy and similarity measure. By using Lagrange Multiplier Method and closeness degree, we develop a novel single-valued neutrosophic MADM method. Finally, a numerical example of selecting the desirable supplier is provided, and the comparison with existing approaches is performed to validate the rationality and effectiveness of the proposed method. Show more

Keywords: Multi-attribute decision making, single-valued neutrosophic sets, entropy, similarity measure

DOI: 10.3233/JIFS-18854

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Davvaz, Bijan | Kim, Yong Chan

Article Type: Research Article

Abstract: In this paper, we introduce the concepts of Alexandrov L -neighborhood filters, Alexandrov L -topologies and Alexandrov L -convergence structures in complete residuated lattices. We investigate the Galois correspondences among Alexandrov L -neighborhood filters, Alexandrov L -topologies and Alexandrov L -convergence structures. Moreover, we investigate their topological properties and give their examples.

Keywords: Complete residuated lattices, Alexandrov L-topologies, Alexandrov L-neighborhood filters, Alexandrov L-convergence structures

DOI: 10.3233/JIFS-181295

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Rashmanlou, Hossein | Pal, Madhumangal | Borzooei, Rajab Ali | Mofidnakhaei, F. | Sarkar, Biswajit

Article Type: Research Article

Abstract: Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. The interval-valued fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they have many applications in networks. In this paper, at first we define three new operations on interval-valued fuzzy graphs namely strong product, tensor product and lexicographic product. Likewise, we study about the degree of a vertex in interval-valued fuzzy graphs which are obtained from two given interval-valued fuzzy graphs using the operations Cartesian …product, composition, tensor and strong product of two interval-valued fuzzy graphs. These operations are highly utilized by computer science, geometry, algebra, number theory and operation research. In addition to the existing operations these properties will also be helpful to study large interval-valued fuzzy graph as a combination of small, interval-valued fuzzy graphs and to derive its properties from those of the smaller ones. Show more

Keywords: Cartesian product, composition, tensor product, lexicographic product

DOI: 10.3233/JIFS-181488

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2018

Authors: Liu, Yue | Cai, Fei | Ren, Pengfei | Gu, Zhizhou

Article Type: Research Article

Abstract: To address the problem that the existing time-aware methods always recommend out-of-fashion items to users, this paper proposes a novel method named Item Life Cycle based Collaborative Filtering (ItemLC-CF), taking both user’s preference and item’s popularity into consideration. This method presents a life cycle function to simulate the variation of item’s popularity and integrates such variation with CF to learn the relative preference for items by reranking the candidate set of CF according to item’s vitality. Given that it is extremely complicated to construct a life cycle function for each item, items are clustered into different categories via their popularities …instead of original product categories. Meanwhile, a SVM ensemble classifier based on AdaBoost is employed to find an appropriate category for new arrival items. Evaluation on MovieLens-1M dataset demonstrates that the proposed method can improve the performance of recommendation list, in turn providing more reasonable and popular recommendation lists for users. Show more

Keywords: Collaborative filtering, item life cycle, recommender system, interest shift

DOI: 10.3233/JIFS-18783

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Rivaz, Azim | Azizian, Mahdieh | Kamyad, Ali Vahidian | Zangoei Zadeh, Somayeh

Article Type: Research Article

Abstract: Mathematical modelling as a useful technique to obtain a better and wider perception of a complex biological subject such as cancer, has been increasingly applied in recent years. Since the parameters of a mathematical model are obtained by observations and measurements, they are exposed to errors and have uncertainty and ambiguity in their nature. In this paper, in order to achieve a more realistic mathematical model of tumor growth, a system of integro-partial differential equations which describes the growth of a tumor characterized by the presence of cancer stem cells - which are the main reason of treatment failure …and tumor relapse - is generalized to a fuzzy integro-partial differential system. Introducing some definitions, several theorems are proved to convert the fuzzy integro-partial differential system to an optimization problem. The proposed new method computes not only the approximate fuzzy solution of the full fuzzy system, but also the difference between the exact and approximate solution. It is further found that the tumor growth paradox appears in the full fuzzy mathematical model of tumor growth as well. Show more

Keywords: Fuzzy mathematical model, tumor growth model, stem cells, fuzzy integro-differential system, tumor growth paradox

DOI: 10.3233/JIFS-18261

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: Daneshpayeh, Roohallah | Borumand Saeid, Arsham | Mirvakili, Saeed | Rezaei, Akbar

Article Type: Research Article

Abstract: In this paper, the notions of orthogonal, dense, regular, zero-divisor, strong and complemented elements in a pseudo BL-algebra are introduced and relation between the orthogonal and zero-divisor elements for perfect (good) pseudo BL-algebras is investigated. In particular, we get some results when a pseudo BL- algebra is good or perfect. Finally, a new characterization of these elements in a pseudo BL-algebra by a diagram is given.

Keywords: Pseudo BL-algebra, (Perfect, Primary) filter, radical, (Orthogonal, Dense, Regular, Zero divisor, Strong, Complemented) elements

DOI: 10.3233/JIFS-181218

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Izhar, Muhammad | Khan, Asghar | Mahmood, Tariq

Article Type: Research Article

Abstract: The main motivation behind this paper is to study some structural properties of a non-associative structure Abel Grassmann’s groupoid (AG-groupoid) in terms of double-framed soft sets (DFS sets) as it hasn’t attracted much attention compared to associative structures. An AG-groupoid can be referred to as a non-associative semigroup, as the main difference between a semigroup and an AG-groupoid is the switching of an associative law. In this paper, we introduce the concept of (M , N )-double-framed soft ideals (briefly, (M , N )-DFS ideal) of AG-groupoids and investigate some properties of these notions. We have shown that every (M …, N )-DFS ideal is (M , N )-DFS AG-groupoid but the converse is not true. This is shown with the help of an example. We also discuss the properties of (M , N )-DFS ideals in regular AG-groupoids. Moreover a decision making algorithm based on DFS-sets is given. Show more

Keywords: DFS set, (M , N)-DFS AG-groupoids, (M , N)-DFS ideal, regular AG-groupoid, choice values, DFS-weighted set

DOI: 10.3233/JIFS-181119

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2018

Authors: Singh, Kuldeep | Singh, Shashank Sheshar | Kumar, Ajay | Biswas, Bhaskar

Article Type: Research Article

Abstract: Mining high utility itemsets (HUIs) is a basic task of frequent itemsets mining (FIM). In recent years, a trend in FIM has been to design algorithm for mining HUIs because FIM assumes that each item can not appear more than once in a transaction and all items have the same importance (weight, unit profit, price, etc.). However, in real-world, items appear more than once in a transaction and also have some importance. HUIs mining considers that items appear with some quantity and importance. Traditional HUIs mining algorithms assume that items have only positive unit profit. However, in real-world, items …may appear with negative unit profit also. For example, it is common that a retail store sells items at a loss to stimulate the sale of other related items or simply to attract customers to their retail location. Therefore, items occur with negative unit profit or negative utility. To consider negative unit profit, HUIs with negative utility has been introduced. This paper surveys recent studies on HUIs mining with negative utility and their applications. The main goal is to provide a survey of recent advancements and research opportunities. This paper presents key concepts and terminology related to HUIs mining with negative utility. This presents a taxonomy of all the algorithms consider negative utility. To the best of our knowledge, this is the first survey on the mining task of HUIs with negative utility. The paper also presents research opportunities and the challenges in HUIs mining problems. Show more

Keywords: High utility itemsets mining, utility mining, negative utility

DOI: 10.3233/JIFS-18965

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Bi, Lvqing | Dai, Songsong | Hu, Bo | Li, Sizhao

Article Type: Research Article

Abstract: A complex fuzzy set, characterized by complex-valued membership functions, is a generalization of a fuzzy set. In this paper, we present complex fuzzy arithmetic aggregation (CFAA) operators, complex fuzzy weighted arithmetic aggregation (CFWAA) operators. Based on the partial ordering of complex fuzzy values, we develop complex fuzzy ordered weighted arithmetic aggregation (CFOWAA) operators. Highly pertinent to complex fuzzy operations is the concept of rotational. This concept has been developed for complex fuzzy aggregation operators. We show that CFAA, CFWAA and CFOWAA operators possess the property of rotational invariance. Moreover, based on the relationship between Pythagorean membership grades and complex …numbers, these operators are studied under Pythagorean fuzzy values. Show more

Keywords: Complex fuzzy sets, complex fuzzy arithmetic aggregation (CFAA) operators, complex fuzzy ordered weight arithmetic aggregation (CFOWAA) operators, complex fuzzy ordered weight arithmetic aggregation (CFOWAA) operators, pythagorean fuzzy sets

DOI: 10.3233/JIFS-18568

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2018

Authors: Lee, Woongsup | Kim, Kang-Hwi | Tae Han, Hyeon | Choi, Heechul | Ham, Younghwa | Ban, Tae-Won

Article Type: Research Article

Abstract: Understanding factors affecting growth rates in swine is important in the productivity of pig farms. We herein propose machine learning-based schemes to predict the average daily gain (ADG) of pig weight using temperature, humidity, feed intake, and the current weight of the pig. In order to address the lack of available growth data for pigs, we generate a synthetic dataset describing the weight of swine in relation to environmental factors based on the theoretical growth model and experimentally measured data, in an attempt to facilitate the application of machine learning techniques. Using the generated growth data, linear regression, tree regression, …adaptive boosting (AdaBoost), and a deep neural network (DNN) are applied to estimate ADG. By means of a performance evaluation, we confirm that the machine learning algorithms are capable of predicting the ADG of swine accurately even when the growth characteristics of pigs are heterogeneous, i.e., each pig follows a different growth curve. Moreover, we also find that DNN can provide a higher predictive accuracy than other machine learning-based schemes. Show more

Keywords: Average daily gain, swine, machine learning, prediction, deep learning

DOI: 10.3233/JIFS-169869

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Yin, Shi | Li, Baizhou | Dong, Hengmin

Article Type: Research Article

Abstract: In recent decades, many multi-attribute decision-making methods have not been effectively applied to solve practical problems because of various shortcomings. The purpose of this paper is to develop a novel dynamic multi-attribute decision-making (DMADM) method based on the improved weights function and score function. In this paper, a novel method based on the improved entropy of interval-valued intuitionistic fuzzy sets is applied to calculate attribute weight. A time weight method is developed via the multi-target nonlinear programming model based on the ideal solution and information entropy. The influence of decision-makers’ subjective preference and objective attribute information are integrated into …the time weight. A novel ranking method based on the improved score function is used to select the best alternative in the DMADM process. Moreover, the interaction among attributes is considered by the interval-valued intuitionistic fuzzy geometric weighted Heronian means operator in the proposed method. Finally, an example of partner selection with collaborative innovation is given to verify the developed approach. This study contributes to the development of DMADM theory by using improved attribute weight, time weight, and score functions, and offers us a very useful way to deal with DMADM problems in real life. Show more

Keywords: Multi-attribute decision-making (MADM), attribute weight, time weight, score function, collaborative innovation

DOI: 10.3233/JIFS-171505

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Hasnat, Abul | Barman, Dibyendu

Article Type: Research Article

Abstract: Image compression is a process that reduces memory space required to store an image. The image compression techniques are broadly classified into two categories a) Lossless technique b) Lossy technique. Lossy compression technique achieves higher result, but due to data loss it may cause spatial inconsistency, blocking artifact, quantization noise in the decompressed image degrading the image quality. Most of the existing compression techniques are applicable on single image separately. In this study an image compression method is proposed where multiple images of the same size are combined together and compressed to achieve higher compression ratio while keeping image quality …as close as standard image compression techniques. Luminance channel of each image is compressed separately using Vector Quantization (VQ) algorithm while two chrominance channels, Cb and Cr of all images are combined into a three dimensional matrix that forms training vector. Clustering is applied on the training vector to get the initial color representatives. Thus, for the chrominance channels of n number of images, the proposed method generates one index matrix and one centroid matrix of size 56×2× n where 256 is the number of clusters. This centroid matrix contains one 56×2 dimensional centroid matrix for each individual image. This 56×2 matrix contains centroid of each cluster. The centroids of each and every cluster of an image are updated individually using optimization technique to get a better centroid (Cb, Cr) pair. This process updates the color representative pair of Cb and Cr further. This method has been applied on standard images in literature and images collected from UCID v. 2 color image database. Experimental results are analyzed in terms of PSNR and space reduction. Experimental results show that the proposed method achieves a higher compression ratio retaining almost similar image information as other standard lossy compression algorithm. Show more

Keywords: Color image quantization, de-correlated color space, JPEG, K-Means clustering, lossless compression, lossy compression, optimization, PSNR, Vector Quantization, YCbCr

DOI: 10.3233/JIFS-18360

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2018

Authors: Prabhu, S. | Flora, T. | Arulperumjothi, M.

Article Type: Research Article

Abstract: Let G (V , E ) be a Graph. A set W ⊆ V of vertices resolves a graph G if every vertex of G is uniquely determined by its vector of distances to the vertices in W . The metric dimension of G is the minimum cardinality of a resolving set. By imposing different conditions on W we get conditional resolving sets. A resolving set W is said to be an independent resolving set if W contains isolated vertices. Independent resolving number denoted by ir (G) is referred to its …cardinality. In this paper we investigate independent resolving number for Titanium dioxide Nanotube. Show more

Keywords: Metric dimension, independent resolving set, independent resolving number, Titanium dioxide, Nanotube, Nanostructure

DOI: 10.3233/JIFS-181314

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-5, 2018

Authors: de Jesús Martínez Felipe, Miguel | Manuel Felipe Riverón, Edgardo | Alberto Martínez Castro, Jesús | Pogrebnyak, Oleksiy

Article Type: Research Article

Abstract: In this paper, the problem of image block similarity measuring in noisy environment is considered. In different practical applications often is necessary to find groups of similar image blocks within an ample search area. In such situation, the full search algorithm is very slow; apart, its accuracy is low due to the presence of noise. New algorithms for similar image block matching in noisy environment are presented. The algorithms are based on the dissimilarity measure calculated as the distance between image patches in the discrete cosine transform domain. The proposed algorithms perform the hierarchical search for the similar image blocks …and hereby have a reduced complexity in comparison to the full search algorithm. Adjusting the radius of the distance calculation for spectral coefficient matching, the characteristics of the block matching algorithm can easily be adjusted to obtain a better accuracy of the matched block group. A higher accuracy is obtained using the local adaptation of the radius for the distance calculation outperforming the existing algorithms used to find groups of similar blocks in different applications, such as image noise filtering and image clustering. The performance of the different block matching algorithms were evaluated on the base of the proposed accuracy measure that uses as a reference the list of patches obtained with the full search algorithm in the absence of noise. Show more

Keywords: Dissimilarity measure, noisy image block matching, discrete cosine transform, hierarchical search, local adaptation

DOI: 10.3233/JIFS-18533

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: Kutlu Gündoğdu, Fatma | Kahraman, Cengiz | Civan, Hatice Nida

Article Type: Research Article

Abstract: EDAS (Evaluation Based on Distance from Average Solution) is based on the distances of each alternative from the average solution. It is similar to other distance based multi-attribute decision-making methods such as TOPSIS and VIKOR. Hesitant fuzzy sets are an extension of ordinary fuzzy sets where the hesitation arises in the assignment of membership degrees of the elements to a fuzzy set. In this paper, we extend classical EDAS method to its hesitant fuzzy version in order to capture decision makers’ hesitancies. The proposed Hesitant Fuzzy Evaluation Based on Distance from Average Solution (HF-EDAS) is based on different aggregation operators …with defuzzification and without-defuzzification processes, which is presented by four HF-EDAS versions. The proposed method has been applied to a multi-criteria and multi-expert hospital selection problem for organ transplantation. Additionally, we present a comparative analysis with hesitant fuzzy TOPSIS (HF-TOPSIS). The results show that HF-EDAS selects the same best alternative as HF-TOPSIS. However, the proposed versions of HF-EDAS indicated some slight changes in the ranking of alternatives. Show more

Keywords: EDAS, multi-criteria decision making, hesitant fuzzy sets, service quality, hospital selection

DOI: 10.3233/JIFS-181172

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Li, Yonghong | Li, Jiang

Article Type: Research Article

Abstract: In this paper, the judgment of fuzzy bases of a closed G-V fuzzy matroid is studied and a necessary and sufficient condition of judging fuzzy bases is presented. Based on the results, an intuitive tree structure of a closed G-V fuzzy matroid is proposed and some of its properties are obtained.

Keywords: Fuzzy sets, matroids, fuzzy matroids, fuzzy bases, tree structure

DOI: 10.3233/JIFS-172267

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: Qu, Guohua | Li, Tianjiao | Zhao, Xia | Qu, Weihua | An, Qianying | Yan, Junai

Article Type: Research Article

Abstract: In this paper, a stochastic decision making method based on regret theory and group satisfaction is proposed with unknown attribute weights and dual hesitant fuzzy elements. Considering that the decision makers have different levels of satisfaction with the alternatives, first of all, according to the score function and the accuracy function of dual hesitant fuzzy elements, a novel group satisfaction degree function of dual hesitant fuzzy elements is defined. And then, an attribute weight optimization model based on the new group satisfaction degree of dual hesitant fuzzy elements is established and the Lagrange function is constructed to obtain the attribute …weights. Secondly, on the basis of the regret theory, the regret and rejoice valued matrices of the program are given, and then the ranking values of each alternative can be obtained by combining with the weight of the attribute. Finally, a numerical example is given to illustrate the applicability and feasibility of the proposed method. Show more

Keywords: Dual hesitant fuzzy element, regret theory, group satisfaction degree, stochastic decision making

DOI: 10.3233/JIFS-18667

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Nie, Cuiping | Nie, Tao | Sun, Hongxia

Article Type: Research Article

Abstract: This paper proposes the H-average tree solution based on a graph game with fuzzy characteristic function. This solution is a generalization of the classical average tree solution, and is an imputation of a graph game with fuzzy characteristic function. When the game is cycle-free the H-average tree solution is the unique solution that satisfies component efficiency and component fairness. The interval average tree solution is introduced. Furthermore, we show the relationship between the H-average tree solution and the interval average tree solution. A practical application of the proposed model in outsource production is given.

Keywords: Graph game with fuzzy characteristic function, H-average tree solution, imputation, interval average tree solution

DOI: 10.3233/JIFS-17502

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2018

Authors: Jain, Parul | Dixit, Veer Sain

Article Type: Research Article

Abstract: Context Aware Recommender Systems exploit specific situation of users for recommendations, hence are more accurate and satisfactory. Neighborhood based collaborative filtering is the most successful approach in this area owing of its simplicity, intuitiveness, efficiency and domain independence. The key of this approach is to find similarity between users or items using user–item–context rating matrix. Typically, context aware datasets are highly sparse since there are not enough or no preferences under most contextual conditions. Traditional similarity measures such as Pearson correlation coefficient, Cosine and Mean squared difference suffer from co-rated item problem and do not consider contextual conditions of the …users. Therefore, these measures are not effective for sparse datasets. Therefore, the aim of this paper is to propose a new similarity measure and its variants based on Bhattacharyya Coefficient which are suitable for sparse datasets weighted by contextual similarity. Subsequently, we have applied them in neighborhood based algorithms where each component is contextually weighted. The experiments are performed on two contextually rich datasets which are especially designed to do personalization research instead traditional well known datasets. The results for Individual and Group recommendations indicate that the proposed similarity measure based algorithms have significantly increased the accuracy of predictions over traditional Pearson correlation coefficient measure based algorithms. Show more

Keywords: Bhattacharya coefficient, Neighborhood based collaborative filtering, Contextual similarity, Sparse datasets, Group recommendations

DOI: 10.3233/JIFS-18341

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Yang, Jinxin | Tang, Xiaoan | Yang, Shanlin

Article Type: Research Article

Abstract: Hesitant fuzzy set theory provides an effective technique for researchers and engineers to cope with vagueness and uncertainty. In recent years, to explore the correlation between hesitant fuzzy sets, traditional correlation measure in statistics has been constantly studied in hesitant fuzzy environments. In this study, extant studies of correlation measures in hesitant fuzzy contexts are recalled and analyzed. In view of the forgoing analysis, we find out that the extant correlation coefficients have some limitations. Moreover, a few correlation coefficients are not in line with the traditional definition of correlation coefficients. In order to address the flaws of the existing …proposals, a novel hesitant fuzzy correlation coefficient is proposed in this study. The new proposal of this study can not only overcome the flaws of the old hesitant fuzzy correlation coefficients, but it also shows several desirable characteristics. The weighted form of the newly defined correlation coefficient and its features are also investigated. Finally, three numerical examples concerning supplier selection and medical diagnosis are examined using the developed correlation coefficients to demonstrate their applicability. Comparison analyses with existing proposals highlight the efficiency of our proposals. Show more

Keywords: Correlation coefficient, hesitant fuzzy sets, decision making, supplier selection, medical diagnosis

DOI: 10.3233/JIFS-181393

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2018

Authors: Moral-García, S. | Mantas, Carlos J. | Castellano, Javier G. | Abellán, Joaqu’ın

Article Type: Research Article

Abstract: Binary Relevance (BR) is a simple and direct approach to the Multi-Label Classification (MLC). It decomposes the multi-label problem into several binary problems, one per label. It uses an algorithm of traditional supervised classification in order to solve these binary problems. On the other hand, Credal C4.5 (CC4.5) is a modification of the classical C4.5. CC4.5 estimates the probability of the class variable by using imprecise probabilities. In the literature, this new classification algorithm has obtained better results than C4.5 when both have been applied on datasets with class noise. In MLC, since there are not just a class, but …multiple labels are disposed, it is more probable that there is intrinsic noise than in traditional classification. From the previous reasons, in this work it is studied the performance of BR using Credal C4.5 as base classifier versus BR with C4.5. It is carried out an experimental study with several muti-label datasets and a considerable number of measures for MLC. This study shows that the performance of BR is improved when it uses CC4.5 as base classifier versus BR with C4.5. In consequence, it is probably suitable to apply imprecise probabilities in Decision Trees within the MLC field too. Show more

DOI: 10.3233/JIFS-18746

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Sathiya, B. | Geetha, T.V.

Article Type: Research Article

Abstract: Ontologies are the extensively used structural and semantic knowledge representation to describe any entities with non-ambiguous meaning and relations. A large number of general and domain specific semantic similarity measures are available in the literature to access the similarity among these rich knowledge bases. Nevertheless, none of the measures have the best performance in all domains and applications. Each measure uses different strategies and possesses its own pros and cons. Hence, to consolidate the different kinds of measures, its applicability, the similarity and difference among them, the advantages and disadvantages of the measures, a detailed review of different semantic similarity …measures has been carried out in this paper. Specifically, a comprehensive and novel classification of the semantic similarity measures exploring different type of ontology information has been presented and each measure is briefed. Further, the open challenges in this field, existing evaluation methodologies and datasets for the semantic similarity measures are also described. Show more

Keywords: Semantic similarity, ontologies, path based measures, depth based measures, IC based measures, DL based measures, feature based measures

DOI: 10.3233/JIFS-18120

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2018

Authors: Rizvi, Naela | Ramesh, Dharavath

Article Type: Research Article

Abstract: Cloud computing relates to the storage and accessing of data as a service from Internet for any organizational infrastructure at-any-time. The delivery of some of the services related to computing such as servers, networking, storage, software, etc., is made possible with the use of cloud computing. Companies offer these services in terms of cloud service providers (CSPs) who charge for the services they provide to the users. When a request is made to use the services, the service provider allocates a feasible number of virtual machines (VMs). Determining optimum amount of resources required at runtime to satisfy the user’s …request is not a trivial task. Therefore, in cloud ecosystem the cardinal issue is the management of resource allocation to an application in order to abide by the service level agreements (SLAs). The fundamental objective of cloud service management is to design a self-adjustable auto-scalar to respond to elastic workload and optimizing the allocation of resources with reduced cost. The notable issue is how and at what time resources are to be allocated/de-allocated in order to follow agreed SLAs. In this paper, we propose a resource provisioning framework based on the integrated concepts of autonomic computing with Fuzzy Q Learning and Chebyshev’s Inequality principle. The concept of auto-scaling mechanism is commonly implemented in four phases of proposed autonomic MAPE loop framework: Monitoring, Analysis, Planning and Execution. The proposed framework follows the control MAPE loop structure with the inclusion of Chebyshev’s inequality for prediction in the analysis phase and fuzzy Q-learning in planning phase, where human intervention in the form of fuzzy rules ensures efficacious provisioning of VMs. A comparative analysis has been performed with a different combination of (i) LRM in the analysis phase with FBQ-LA in planning phase, ii) Chebyshev’s Inequality in the analysis phase with FBQ-LA in planning phase, and iii) Chebyshev’s Inequality in the analysis phase with Q-Learning in planning phase. Experimental results prove that the proposed autonomic model based on Chebyshev’s inequality and FBQ-LA outperforms the existing model in terms of improved VM provisioning, minimized costs as well as reduction in response time. Show more

Keywords: Resource provisioning, autonomic computing, MAPE loop, fuzzy Q-learning, Q-learning

DOI: 10.3233/JIFS-18828

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Owolabi, Taoreed O. | Gondal, Mohammed A.

Article Type: Research Article

Abstract: Laser induced breakdown spectroscopy (LIBS) is an excellent technique for analysis of solid and liquid samples. However there are inherent problems with concentration determination of elements present in the test sample with better accuracy. In order to address this challenge, hybrid fusion of extreme learning machine (ELM) and support vector regression (SVR) is proposed for the first time. Extreme learning machine (ELM) is a non-linear chemo-metric method which has inherent capacity to approximate any non-linear relation describing the laser induced plasma. However, ELM surfers from over-fitting which affects its accuracy for spectroscopic regression. On the other hand, SVR is a …non-linear chemo-metric tool based on statistical learning theory and overcomes the problem of over-fitting by proper tuning of its hyper-parameters. The merits of both chemo-metrics are harnessed in this work and implemented for quantitative analysis of LIBS spectra of seven standard bronze samples. The performance of ELM-SVR model which uses the output of ELM as its input is compared to that of SVR-ELM model which takes the output of SVR as its input. The hyper-parameters of the proposed models are optimized using gravitational search algorithm (GSA). On the bases of root mean square error (RMSE) as a measure of model performance, ELM-SVR performs better than SVR, ELM and SVR-ELM model with performance improvement of 95.76%, 89.33% and 52.71%, respectively. The accuracy of the proposed hybrid models would be of immense significance for quick quantitative analysis in LIBS and eventually promotes wide applicability of the technique. Show more

Keywords: LIBS spectra, extreme learning machine, gravitational search algorithm, support vector regression, quantitative analysis, hybrid model

DOI: 10.3233/JIFS-171979

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Hong, Jie | Qin, Xiansheng | Li, Jing | Niu, Junlong | Wang, Wenjie

Article Type: Research Article

Abstract: Over the past two decades, motor imagery brain-computer interface (MI-BCI) system has been extensively developed. In this system signal processing algorithms are critical to robust operation. In BCI community, however, there is no comprehensive review of the recent development of signal processing algorithms. Through analyzing the latest papers, signal processing algorithms of pre-processing, feature extraction, feature selection, and classification components are discussed in detail. Besides, post-processing and other existing problems are mentioned. The following key issues are addressed: (1) which components are the key of signal processing; (2) which signal processing algorithms are frequently used in each component; (3) which …signal processing algorithms attract more attention. This information can be used as reference and guidance for further research. Show more

Keywords: Motor imagery brain-computer interface (MI-BCI), signal processing algorithms, pre-processing, feature extraction, classification

DOI: 10.3233/JIFS-181309

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2018

Authors: Ooi, Boon Pin | Abdul Rahim, Norasmadi | Zakaria, Ammar | Masnan, Maz Jamilah | Abdul Shukor, Shazmin Aniza

Article Type: Research Article

Abstract: Under certain situations, researchers were forced to work with small sample-sized (SSS) data. With very limited sample size, SSS data have the tendency to undertrain a machine learning algorithm and rendered it ineffective. Some extreme cases in SSS problems will have to deal with large feature-to-instance ratio, where the high number of features compared to small number of instances will overfit the classification algorithm. This paper intends to solve small sample-sized classification problems through hybrid of random subspace method and random linear oracle ensemble by utilizing binary feature subspace splitting and oracle selection scheme. Experimental results on artificial data indicate …the proposed algorithm can outperform single decision tree and linear discriminant classifiers in small sample-sized data, but its performance is identical to k-nearest neighbor classifier due to both shared similar selection approach. Results from real-world medical data indicate the proposed method has better classification performance than its corresponding single base classifier especially in the case of decision tree. Show more

Keywords: Ensemble method, classification, small sample, Euclidian’s distance

DOI: 10.3233/JIFS-18504

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Hu, Bo | Bi, Lvqing | Dai, Songsong | Li, Sizhao

Article Type: Research Article

Abstract: A complex fuzzy set is a set whose membership grades are complex values in the unit circle in the complex plane. This paper introduces the concept of approximate parallelity between complex fuzzy sets based on the phase of complex-valued membership grade. After that, the property of approximate parallelity preserving for complex fuzzy operators and complex fuzzy inference are investigated.

Keywords: Approximate parallelity, approximate parallelity preserving, complex fuzzy sets, complex fuzzy operators, complex fuzzy inference

DOI: 10.3233/JIFS-181131

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2018

Authors: Batyrshin, Ildar

Article Type: Research Article

Abstract: Similarity, correlation and association measures play an important role in statistics, information retrieval, data mining and data science, classification and machine learning, recommender systems and decision-making. They have numerous applications in ecology, social and behavioral sciences, biology and bioinformatics, social network and time series analysis, image and natural language processing. Often the measures with the same name introduced on different domains have different properties, and the measures with the same properties have different names. To unify analysis of measures defined on different domains, this paper considers these measures as functions defined on universal domain and satisfying some sets of properties. …The general properties of similarity functions (SF) and dissimilarity functions (DF) under the joint name of resemblance functions (RF) studied on universal domain and illustrated by examples on specific domains. The known and the new methods of construction of similarity measures are considered. This paper discusses the following aspects of RF: relationship with fuzzy (valued) relations, T-transitivity and triangle inequality, Minkowski distance and data transformation, cosine SF, RF on domains with involution (negation), aggregation and transformations of RF, visualization of RF. The paper considers also the lattice of RF, composition and min-transitive transformations of SF (fuzzy proximity relations), applications to hierarchical clustering and non-probabilistic entropy of RF. In addition, the paper proposes the method of construction of correlation functions (association measures) using SF. Pearson correlation and Yule’s Q association coefficients obtained as particular cases of the general method. One can use the paper as a survey of works on similarity and dissimilarity measures on specific domains, as a guide for constructing new similarity and correlation measures, as a base for the study of mathematical properties of resemblance functions on universal and specific domains, and also as a part of the course on Data Science. Show more

Keywords: Association, similarity, dissimilarity, correlation, distance, transitivity, negation, data mining, data science

DOI: 10.3233/JIFS-181503

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-28, 2018

Authors: Sánchez, Octavio | Sierra, Gerardo

Article Type: Research Article

Abstract: This article introduces a different method for text representation in order to perform clustering over different articles which, arguably, has no subjective information with similar topic-sentiment use of language. Using the joint sentiment/topic model, the text is vectorized in a low dimensional space. These vectors were then used as distance measurement for clustering texts. While comparing this unusual method with a traditional bag ofwords representation an improvement in the performance of the algorithms was observed. The authors think this method of representation might have implications for future studies of the computational interpretation of texts.

Keywords: Text representation, Joint Sentiment Topic Modeling, text clustering

DOI: 10.3233/JIFS-18530

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Heidari, S.V. | Soleimani, S. | Faghihi, F. | Mozaffari, B.

Article Type: Research Article

Abstract: The current study presents a new method for allocation of the contribution of voltage harmonic distortion for consumers and utilities. This method utilizes three-phase voltage and current waveforms at the point of common coupling (PCC) by applying an adaptive Kalman filter to estimate the amplitude and phase angle of the waveform. The fuzzy adaptation part of the Kalman filter allows resetting of the Kalman gain for fast tracking of system variations under transient conditions. Singular value decomposition based on recessive least square is used to estimate the Norton equivalent circuit for the entire system. In the proposed method an Indicator …of the voltage value is used to determine the contribution of harmonic distortion for both sides. The characteristics of the proposed method were investigated through simulation of a nonlinear load which is connected to the distribution system and practical data from 130 kV distribution system in north-west of Iran. Show more

Keywords: Harmonic component contributions, fuzzy system, kalman filter, distribution system

DOI: 10.3233/JIFS-172055

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Moradi, Mojtaba | Hafezalkotob, Ashkan | Ghezavati, Vahidreza

Article Type: Research Article

Abstract: Sustainability is one of the most significant problems in today’s world and the concept of sustainable development is being an important objective in construction projects. Since the large projects have enormous and different activities that should be scheduled by considering resource constraint and precedence relationship between them, the resource-constrained project scheduling problem (RCPSP) is a NP-hard problem. In this study, fuzzy project scheduling model is presented to solve RCPSP under uncertainty in availability of the resources and activities duration simultaneously. Subcontractors have incentive to share their resources in the form of coalition in order to reduce activities time and cost. …In this research, cooperative game methods are introduced for fair allocating utility of the project, as well as, present supper-additivity, stability and satisfaction level of each coalition. Finally, sustainability concept is analyzed in RCPSP and cooperation of subcontractors in a coalition form, whereas in the previous researches these topics addressed separately or generally in project scheduling to minimize the makespan and maximize the profit of project. The results of the proposed model indicate that the subcontractors can obtain more profit and the balance between sustainability indicators in project management arises by collaboration. Show more

Keywords: Sustainability, fuzzy project scheduling, RCPSP, cooperative game theory, satisfaction level

DOI: 10.3233/JIFS-171821

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Hussain, Basharat | Nawaz, Shah | Yousaf, Muhammad Haroon

Article Type: Research Article

Abstract: Real-time vehicle detection is one of the challenging problems for automotive and autonomous driving applications. Object detection using Deformable Parts Model (DPM) proved to be a promising approach providing higher detection accuracy. But the baseline DPM scheme spends 98% of its execution time in loop processing thus highlighting the drawback of higher computational cost for real time applications. In this paper, we have proposed a real time vehicle detection scheme for a low-powered embedded Graphics Processing Unit (GPU). The proposed scheme is based upon DPM approach using CUDA programming with different parallelization and loop unrolling schemes to reduce computational cost …of DPM. Three loop unrolling schemes i.e. loosely unrolled, tightly unrolled and hybrid unrolled is proposed and implemented on two different datasets. Finally, we provided an optimal solution for vehicle detection with minimum execution time without having any impact on vehicle detection accuracy. We achieved a speedup of 3x to 5x as compared to state-of-the-art GPU implementation and 30x as compared to baseline CPU implementation of DPM on a low-powered automotive-grade embedded computing platform which features a Tegra K1 System on Chip (SOC), thus getting advantage of improved efficiency through parallel computation of CUDA. Show more

Keywords: Automous driving, GPU programming, vehicle detection, computer vision

DOI: 10.3233/JIFS-172303

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Liu, Peide | Xu, Hongxue

Article Type: Research Article

Abstract: For a multi-attribute group decision making (MAGDM) problem where the attribute values are intuitionistic uncertain linguistic variables (IULVs), we propose a novel decision making method based on hybrid aggregation operator of IULVs. Firstly, new operational rules of IULVs are proposed based on linguistic scale functions (LSFs) to overcome the existing shortcoming in which the operations on linguistic variables (LVs) directly based on the subscripts of linguistic terms (LTs) are not closed, then the expected value and accuracy function of IULVs are introduced. Further, some aggregation operators for IULVs are proposed, including the weighted geometric average operator for IULVs (IULWGA), ordered …weighted geometric operator for IULVs (IULOWG), then the hybrid geometric operator for IULVs (IULHG) are developed, which could consider the weights of attributes and their ranking positions. However, because IULHG don’t meet some desirable properties, we proposed a new hybrid weighted geometric operator for IULVs (IULHWG) which can not only weight the importance of each argument and its ordered position but also maintain some desirable properties. Based on these operators, an approach to MAGDM with IULVs has been proposed. Finally, an illustrative example is provided to show the steps of the developed approach and to demonstrate its practicality and effectiveness. Show more

Keywords: Linguistic variables, intuitionistic fuzzy set (IFS), MAGDM, aggregation operator

DOI: 10.3233/JIFS-172305

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2018

Authors: Hartono, Pitoyo | Trappenberg, Thomas

Article Type: Research Article

Abstract: In recent years, machine learning especially deep models have made significant improvements over their performances and thus applicable to many problems that until a decade ago were prohibitively difficult to learn. One of the strengths of the deep models is that they adaptively capture well-structured representations of the input in their internal representations that help them to generate desirable outputs. However, while many studies are dedicated for improving the performances of neural networks, less efforts are focused for understanding the formation of the internal representations in hierarchical neural networks and the implications to their performances. Here, we study a network …model that incorporates topographical self-organizing maps into a supervised network and show how gradient learning results in a form of a self-organizing learning rule. Topographical self-organizing principles as internal representation is interesting because while topographical self-organizing principles have motivated much of early learning models and relevant to biological learning systems, such principles have rarely been included in supervised learning architectures. In this paper our objectives are explaining the dynamics of the proposed model, visually comparing the internal representation of the proposed model against some deep models and importantly showing that our model is robust in the sense of its application to a variety of areas, which is believed to be a hallmark of biological learning systems. Show more

Keywords: Self-Organization, topographic representation, supervised learning, deep neural networks, visualization

DOI: 10.3233/JIFS-18343

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: López-Ortega, Omar | Castro-Espinoza, Félix

Article Type: Research Article

Abstract: This paper presents an account of fuzzy similarity metrics that have been proposed to quantify consensus in Multi Criteria Group Decision Making. Fuzzy similarity metrics are indispensable to determine consensus when experts evaluate alternatives in fuzzy terms, which capture experts’ uncertainty and hesitancy. Furthermore, factors such as the level of expertise or cognitive bias lead to disagreements within the group. The fuzzy similarity metrics described in this article are used to measure the similarity between type 1 and type 2 fuzzy sets, and fuzzy numbers. Consensus can be quantified at three different levels: criteria judgement, alternative judgement, or expert preferences. …Promising future work includes the incorporation of social fuzzy measures under the umbrella of multi-agent systems as well as the analysis of fuzzy intuitionistic sets. Show more

Keywords: Consensus measure, fuzzy distance, aggregation, decision making

DOI: 10.3233/JIFS-18508

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Yaylalı, Gözde | Çakmak Polat, Nazan | Tanay, Bekir

Article Type: Research Article

Abstract: A new soft group definition is given by Ghosh and Samanta by using the definition of soft element which is introduced by Wardowski. In this paper we study on binary operation on a soft set by using the soft element definition. Considering this binary operation which is the generalization of the soft group definition of Ghosh and Samanta we gave the notions such as soft groupoid, soft group, soft ring and some related results are obtained.

Keywords: Soft Set, Soft Element, Soft Group, Soft Ring

DOI: 10.3233/JIFS-171083

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Liang, Chengyu | Li, Fanghui

Article Type: Research Article

Abstract: In this paper, S 0 , S 1 and S 2 separation axioms are introduced in M -fuzzifying convex spaces. Each M -fuzzifying convex space can be regarded to be S 0 , S 1 and S 2 separated to some degree. Some properties of them are investigated. The relations among them are discussed.

Keywords: M-fuzzifying convex spaces, S 0 , S 1 , S 2

DOI: 10.3233/JIFS-171361

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2018

Authors: Liu, Hongbin | Jiang, Le

Article Type: Research Article

Abstract: Multidistance is an extension of conventional distance and is used to measure distance for more than two points. It has been applied to some practical problems since its appearance. In order to enrich the family of multidistances and facilitate further applications of multidistances, a new multidistance based on the generalized OWA (GOWA) operator is introduced in this paper. Some of its properties, including regularity, stability, strong multidistance, super-additivity, homogeneity, are investigated. A power average operator is then proposed, whose support function is calculated by using the proposed GOWA-based multidistance. A numerical example is then presented to show the performance of …this operator. Show more

Keywords: Multidistance, generalized OWA operator, power average operator, support function

DOI: 10.3233/JIFS-172140

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2018

Authors: Warrens, Matthijs J.

Article Type: Research Article

Abstract: 2 × 2 tables are encountered in various scientific disciplines, including biomedical, social and behavioral sciences, economics and ecology. In the literature many different similarity measures have been proposed that can be used to further summarize the information in a 2 × 2 table. Many of these measures are just functions of the four cells. In this paper the important ones are reviewed. Furthermore, it is shown how various similarity measures are related to one another by considering certain general similarity measures that have various important similarity measures as special cases. The presented overview may provide insights that may …be helpful to researchers from various scientific disciplines in deciding what similarity measure to use in applications or for studying theoretical properties. Show more

Keywords: Binary variables, presence/absence data, comparing partitions, agreement indices, association coefficients

DOI: 10.3233/JIFS-172291

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2018

Authors: Kamacı, Hüseyin

Article Type: Research Article

Abstract: In this paper, the symmetric difference operation for each of the soft sets and the soft matrices is defined and then their related properties are derived. Also, the concept of similarity measure for the soft matrices is introduced. Thus, we pioneer the budding phase of the use of soft matrices to find the similarity of soft sets. Through the soft matrices, we develop the Scilab code which facilitates the computation process of similarity measure among the soft sets composed of many parameters and alternatives. Moreover, it is shown with several examples that the similarity measure can be used for some …cases involving the uncertainties in various areas. To confirm the consistency of the emerging similarity measure, we make comparisons with the preexisting similarity measures for the soft sets. Show more

Keywords: Soft set, soft matrix, symmetric difference, similarity measure, significantly similar

DOI: 10.3233/JIFS-18339

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Zhang, Qibin | Wang, Peng | Chen, Zonghai

Article Type: Research Article

Abstract: This paper presents a novel qualitative scan matching approach based on the point cluster representation of laser scans for the coordination of mobile robots in indoor environments. According to the geometric characteristics of the scanned environment, a hierarchical clustering method is proposed to split the points in a laser scan into stable clusters, with which the point distribution in the scan can be approximated by a collection of probability distributions instead of the discrete data points. Based on the proposed compact and continuous description of captured sensor data, the pairwise constraints between clusters are exploited as heuristic information for efficient …data association between consecutive scans. In order to find the relative transformation between two frames, a qualitative estimate of the rotation with the maximum support and a closed-form solution for the translation are derived. Experiments in a variety of scenarios demonstrate the effectiveness of the proposed approach for robot pose estimation in indoor environments. Show more

Keywords: Mobile robots, pose estimation, laser scan matching, clustering, association

DOI: 10.3233/JIFS-18020

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2018

Authors: Liu, Jiubing | Zhou, Xianzhong | Huang, Bing | Li, Huaxiong | Ju, Hengrong

Article Type: Research Article

Abstract: In the study of intuitionistic fuzzy clustering, the construction of an intuitionistic fuzzy similarity matrix (IFSM) is a fundamental and important issue in the direct clustering analysis, since it determines clustering results and computational efforts. Many methods based on the axioms of intuitionistic fuzzy similarity relations are applicable to IFSM construction. However, most of existing methods may yield a “counterintuitive result” in some cases and consume much computational time. In this paper, we propose a novel intuitionistic fuzzy clustering method to deal with such problems. First, based on the normalized Hamming distance, we define a similarity measure between intuitionistic fuzzy …numbers (IFNs), by which a similarity measure between intuitionistic fuzzy sets (IFSs) is induced. Second, a divergence measure between IFSs is obtained by extending the dissimilarity of IFNs. Third, we construct an IFSM by using together the similarity and divergence measures so as to cluster the intuitionistic fuzzy information. Finally, two examples are presented to show the effectiveness and advantages of our method. Show more

Keywords: Intuitionistic fuzzy sets, similarity measure, divergence measure, intuitionistic fuzzy similarity matrix, clustering analysis

DOI: 10.3233/JIFS-18427

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2018

Authors: Han, Yuan-liang | Shi, Fu-gui

Article Type: Research Article

Abstract: In this paper, the degree of which an L -subset is an L -convex fuzzy ideal is proposed and its some characterizations are given. Besides, an L -fuzzy convexity on a lattice is naturally proposed and its some properties are studied.

Keywords: L-convex fuzzy ideal, Implication operator, L-fuzzy ideal degree, L-fuzzy convexity

DOI: 10.3233/JIFS-18764

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2018

Authors: Kelishami, Hasan Barzegar | Fariborzi Araghi, Mohammad Ali | Allahviranloo, Tofigh

Article Type: Research Article

Abstract: In this paper, by using the fuzzy CESTAC method and the CADNA library a procedure is proposed to control the step size for solving the fuzzy differential equation with fuzzy boundary conditions based on the finite differences method under generalized H-differentiability (gH-differentiability). An algorithm is presented to implement the discrete stochastic arithmetic for solving the given fuzzy boundary value problem on the C++ code via the CADNA library. Also, a theorem is proved to show the accuracy of results based on the concept of the common proximity of two fuzzy numbers. Finally, some examples are solved by using the proposed …algorithm to illustrate the effectiveness of applying the stochastic arithmetic (SA) in place of the floating-point arithmetic (FPA) to validate the results and find the optimal solution. Show more

Keywords: Finite differences method, Fuzzy boundary value problem (FBVP), Stochastic arithmetic, CESTAC method, CADNA Library

DOI: 10.3233/JIFS-181055

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Cui, Wenhua | Ye, Jun | Shi, Lilian

Article Type: Research Article

Abstract: To describe the linguistic neutrosophic information with uncertain variables in the complex decision-making problems, this paper originally defines the concept of a linguistic neutrosophic uncertain number (LNUN). The LNUN consists of three uncertain linguistic variables given by three neutrosophic linguistic numbers to describe the truth, falsity, and indeterminacy linguistic information independently. Then, both the basic operational laws of LNUNs and the score and accuracy functions of LNUNs are presented for the ranking of LNUNs. After that, two operators including a LNUN weighted arithmetic averaging (LNUNWAA) operator and a LNUN weighted geometric averaging (LNUNWGA) operator are developed to aggregate LNUN information. …Based on the aggregation operators, a novel multiple attribute group decision-making (MAGDM) method is established under a LNUN environment. Finally, an example of investment decision is illustrated to demonstrate the application and the effectiveness of the developed method. Show more

Keywords: Linguistic neutrosophic uncertain number, linguistic neutrosophic uncertain number weighted arithmetic averaging operator, linguistic neutrosophic uncertain number weighted geometric averaging operator, score function, accuracy function, multiple attribute group decision-making, neutrosophic linguistic number

DOI: 10.3233/JIFS-18331

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2018

Authors: Xu, Yuan | Shang, Xiaopu | Wang, Jun | Zhang, Runtong | Li, Weizi | Xing, Yuping

Article Type: Research Article

Abstract: The recently proposed picture fuzzy set (PFS) is a powerful tool for handling fuzziness and uncertainty. PFS is characterized by a positive membership degree, a neutral membership degree, and a negative membership degree, making it more suitable and useful than the intuitionistic fuzzy set (IFS) when dealing with multi-attribute decision making (MADM). The aim of this paper is to develop some aggregation operators for fusing picture fuzzy information. Considering the Muirhead mean (MM) is an aggregation technology which can consider the interrelationship among all aggregated arguments, we extend MM to picture fuzzy context and propose a family of picture fuzzy …Muirhead mean operators. In addition, we investigate some properties and special cases of the proposed operators. Further, we develop a novel method to MADM in which the attribute values take the form of picture fuzzy numbers (PFNs). Finally, a numerical example is provided to illustrate the validity of the proposed method. Show more

Keywords: Picture fuzzy set, multi-attribute decision making, aggregation operators, Muirhead mean

DOI: 10.3233/JIFS-172130

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2018

Authors: Ma, Hongzhan | Chu, Xuening | Li, Yupeng

Article Type: Research Article

Abstract: Product redesign strategy can effectively shorten design lead time and reduce production cost of new variants development. Identification of function components is the basis of product redesign. In the existing methods to identify the function components, customer requirements are primarily considered while the failure knowledge, a critical information to improve product reliability, is often ignored. The objective of this research is to identify the to-be-improved components considering both customer requirements and product reliability. First, a two-stage fuzzy quality function deployment (QFD) is used to calculate the importance weight of each component considering customer requirements. Second, the fuzzy failure mode effects …and analysis (FMEA) is adopted to measure the failure risk of each component. Different from traditional FMEA, the failure causality relationships are analyzed in this work to provide a means of making use of failure information more effectively for constructing a directed failure causality relationship diagram. Fuzzy permanent function is developed to quantify the failure risk of each component. Then, a modification necessity index is introduced to model the degree of modification necessity for each component considering customer requirements and failure risk. Finally, the optimal set of function components that need to be modified is identified by 0-1 objective programming and constrained optimization. A case study for identification of the function components for the operation device of a crawler crane is implemented to demonstrate the effectiveness of the developed approach. Show more

Keywords: Identification of function component, fuzzy QFD, FMEA, fuzzy permanent function, 0-1 objective programming

DOI: 10.3233/JIFS-18614

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2018

Authors: Khodsuz, Masume | Seyyedbarzegar, Seyyedmeysam

Article Type: Research Article

Abstract: Surge arresters are essential equipment for power system protection against transient overvoltages. Therefore, their operating condition and fault diagnosis are very important. Leakage current analysis is a conventional method of surge arrester condition monitoring. In this paper, the impacts of disruptive factors on harmonic components of surge arrester current have been evaluated experimentally. Experimental tests have been done on different surge arresters to investigate disruptive factors effects on surge arresters leakage current. To show the ability of introduced indicators, obtained dataset was applied to fuzzy network for recognition task and classification. In order to increase the accuracy of proposed system, …the optimum vector of radius has been found using the optimization algorithm. Bees algorithm, genetic algorithm, imperialist competitive algorithm and particle swarm optimization have been applied to evolve adaptive network based fuzzy inference system. Also the performance of adaptive network based fuzzy inference system has been compared with other classifiers to investigate the capability of the proposed classifier. Results show that the success rates of Bees-ANFIS is higher than the performance of other systems. Show more

Keywords: Surge arrester, harmonics analysis, leakage current, adaptive network based fuzzy inference system, bees algorithm

DOI: 10.3233/JIFS-172040

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Al-Mejibli, Intisar | Ismail, Sura F.

Article Type: Research Article

Abstract: The issues of security and privacy in multimedia data have become of most extreme significance particularly in the applications associated to medical and military sectors. In this paper, an innovative encryption algorithm for real time videos is proposed. The proposed algorithm consists of two phases in both sender and receiver sides. In these two phases, the tasks of compression/encryption and decompression /decryption are performed at sender and receiver sides respectively. The proposal uses H.261 codec in compression/decompression processes and chaotic logistic map system in encryption/decryption processes for private – key generation. The suggested algorithm takes the features of H.261 codec …into consideration to achieve high security with less processing time by encrypt the produced intra frame (I frame) and leaving inter-frame (P-frame) without any changing. Proposed algorithm has innovated new strategy in selecting bytes for encryption by encrypt half of bytes in each I-frame or all of them. Most common statistical tests were performed on the obtained results from applying the proposed algorithm and the results were promising in terms of security level and required time for performing two states. Show more

Keywords: Chaotic logistic map, decryption, encryption, H.261, real-time video

DOI: 10.3233/JIFS-171966

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018

Authors: Agrawal, Divya | Karar, Vinod

Article Type: Research Article

Abstract: Surveillance during low ambient lighting conditions is a challenging task due to hampered perception of the scene while using only visible range cameras. As a solution to this, surveillance using fusion of visible and infrared image has been proposed to provide comprehensive information of the scene instantaneously. Fusion of multispectral sensor information leads to enhancement of information for the operator. However, enhancement of information presented to user not always lead to enhancement of situation awareness (SA) level. This study focuses on SA estimation of operator during ground surveillance tasks while used visible-infrared fused imagery. The original reference image and fused …image outputs are compared statistically using different image quality parameters like target to background entropy, correlation and structural similarity index. A fuzzy based decision model is developed to give a quantitative and qualitative estimate of operator’s SA during surveillance carried out in low ambient lighting conditions. The fuzzy based decision model gives a qualitative estimate of SA as: poor, low, moderate & high, and, quantitative index in range of 1–10 indicating SA level and thus provides alert about the level of details perceivable from the fused image, thereby, helping operator to take decision based on SA index instantaneously. Show more

Keywords: Fuzzy decision system, situation awareness index, assistive technology, surveillance, image fusion

DOI: 10.3233/JIFS-172095

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2018