Journal of Intelligent & Fuzzy Systems - Volume 35, issue 6

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. 35, no. 6, pp. 6199-6215, 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. 35, no. 6, pp. 6217-6227, 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. 35, no. 6, pp. 6229-6239, 2018

Authors: Su, Tai-Sheng | Wu, Chin-Chun | Yang, Huei-Ru

Article Type: Research Article

Abstract: The aims of this paper are to consider cost and energy consumption to solve overhead crane systems’ setting issues. The main issue is that cranes use higher frequency handling equipment in heavy industry. In the overhead crane system setting issues, the determining factors, such as cost, load and energy consumption, are fuzzy. Moreover, decision makers must simultaneously consider real-world conflicting multi-objectives. In summary the question involves a fuzzy multi-objectives problem. Therefore, this paper adopted fuzzy multi-objective programming to construct a mathematical model aimed at minimizing cost and energy consumption with reference to the crane load, recovery period and budget, to …carry out a crane system configuration. The model is used for a real problem to verify its correctness. Finally, this study provides a reference for decision makers to purchase crane device configurations. Show more

Keywords: Fuzzy multi-objective linear programming, overhead crane systems, energy consumption and cost, equipment assignment

DOI: 10.3233/JIFS-171763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6241-6253, 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. 35, no. 6, pp. 6255-6267, 2018

Authors: Senthilkumar, R. | Justin Sunil Dhas, G.

Article Type: Research Article

Abstract: Fractional order proportional, Integral and a derivative controller is a special kind of controller which is used to regulate the output voltage of a class of sepic converter to the desired level. Tuning of fractional Proportional, Integral and Derivative controller (FOPID) is achieved by different metaheuristic algorithm and the optimization performance target is chosen as minimizing the integral square error (ISE). This paper presents a performance analysis of Single Ended Primary Inductance Converter (SEPIC) by time response specifications such as rise time, settling time and steady-state error and further, the results are compared with the controllers designed by Genetic Algorithm …(GA), Particle Swarm Optimization (PSO) and Queen Bee based Genetic Algorithm (QBGA). The design and implementation of fractional order controller for a closed loop control of converter is done by utilizing a MATLAB/SIMULINK environment. Results show that QBGA algorithm exhibit better performance as compared to other optimization technique for voltage mode controller in terms of disturbance rejection. Show more

Keywords: SEPIC converter, fractional PID controller, GA, PSO, QBGA

DOI: 10.3233/JIFS-171892

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6269-6276, 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. 35, no. 6, pp. 6277-6286, 2018

Authors: Heidari, S.V. | Soleymani, 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. 35, no. 6, pp. 6287-6299, 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. 35, no. 6, pp. 6301-6312, 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. 35, no. 6, pp. 6313-6327, 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. 35, no. 6, pp. 6329-6342, 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. 35, no. 6, pp. 6343-6351, 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. 35, no. 6, pp. 6353-6365, 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. 35, no. 6, pp. 6367-6377, 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. 35, no. 6, pp. 6379-6391, 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. 35, no. 6, pp. 6393-6404, 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. 35, no. 6, pp. 6405-6419, 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. 35, no. 6, pp. 6421-6425, 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. 35, no. 6, pp. 6427-6441, 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. 35, no. 6, pp. 6443-6451, 2018

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

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. 35, no. 6, pp. 6453-6460, 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. 35, no. 6, pp. 6461-6468, 2018

Authors: Kouahla, Zineddine | Anjum, Adeel | Seridi, Hamid

Article Type: Research Article

Abstract: Similarity search for content-based retrieval - a sustained problem; many applications endures. Most of the similarity measures intend focusing the least possible set of elements to find an answer. In the literature, most work is based on splitting the target data set into subsets using balls. However, in the era of big data, where efficient indexing is of vital importance, the subspace volumes grow exponentially, which could degenerate the index. This problem arises due to inherent insufficiency of space partitioning interlaced with the overlap factor among the regions. This affects the search algorithms thereby rendering these methods ineffective as it …gets hard to store, manage and analyze the aforementioned quantities. A good topology should avoid biased allocation of objects for separable sets and should not influence the structure of the index. We put-forward a novel technique for indexing; IMB-tree , which limits the volume space, excludes the empty sets; the separable partitions, does not contain objects and creates eXtended regions that will be inserted into a new index named eXtended index , implemented in a P2P environment. These can reunite all objects in one of the subsets-partitions; either in a separable set or in the exclusion set, keeping the others empty. We also discussed the efficiency of construction and search algorithms, as well as the quality of the index. The experimental results show interesting performances. Show more

Keywords: Indexing, eXtended region, parallel, metric space, complex data

DOI: 10.3233/JIFS-18398

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6469-6478, 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. 35, no. 6, pp. 6479-6488, 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. 35, no. 6, pp. 6489-6500, 2018

Authors: Moral-García, Serafín | 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

Keywords: Multi-label classification, Binary Relevance, Credal C4.5, C4.5, imprecise probabilities

DOI: 10.3233/JIFS-18746

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6501-6512, 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. 35, no. 6, pp. 6513-6523, 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. 35, no. 6, pp. 6525-6536, 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. 35, no. 6, pp. 6537-6549, 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. 35, no. 6, pp. 6551-6562, 2018