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

Authors: Wu, Tsu-Yang | Lin, Jerry Chun-Wei | Yun, Unil | Chen, Chun-Hao | Srivastava, Gautam | Lv, Xianbiao

Article Type: Research Article

Abstract:  Association-rule mining (ARM) has concerned as an important and critical research issue in the field of data analytics and mining that aims at finding the correlations among the items in binary databases. However, conventional algorithms considered the frequency of the item(sets) in binary databases for ARM, which is not sufficient in real-life situations. Mining of useful information is not an easy task especially if the item(sets) consist of the added values. Moreover, the discovered knowledge is not easy to understand if you are not the domain experts. For the past decades, several intelligent systems involved the fuzzy-set theory for many …domains and applications due to it is interpretable for human reasoning. Before, the Apriori-based method for discovering fuzzy frequent itemsets (FFIs) based on the type-2 fuzzy-set theory was proposed, which requires the amount of computations with enormous candidates. In this study, we then first present a fast list-based multiple fuzzy frequent itemset mining (named as LFFT2)algorithm under type-2 fuzzy-set theory. It is developed by the type-2 membership functions to retrieve the multiple fuzzy frequent itemsets for presenting more useful and meaningful knowledge for making the efficient strategies or decisions. From the results shown in the experiments, it is clear to see that the developed LFFT2 outperforms the conventional Apriori-based approach regarding the execution time and the number of examined nodes in the search space. Show more

Keywords: Data mining, fuzzy frequent itemset mining, type-2 fuzzy-set theory, list-based structure

DOI: 10.3233/JIFS-179666

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Zhou, Jun | Zhou, Xuan | Liang, Guangchuan | Peng, Jinghong

Article Type: Research Article

Abstract:  Underground natural gas storage (UNGS), usually regarded as one of the most important gas storing and peak shaving method today, has been widely used in various parts of the world. The pipeline gathering system plays a key role in UNGS surface engineering. Thus, optimization of the whole system is crucial to lower the total investment. However, we cannot find that any scholars have published related papers on the gathering pipeline network for UNGS at present. This paper focuses on the two-level star gas field gathering pipeline network construction, establishes a mixed integer nonlinear programming (MINLP) model with considering the injection …and withdrawal process of UNGS. Minimizing pipeline network investment is the object of this model. Constraints of connection mode, platform, pipe length, flow rate, node pressure, pipe diameter are also taken into consideration in this model. A special genetic algorithm is proposed to figure out the optimal topological structure, location of platform and central station, pipe diameter, gas velocity along each pipe of this model. Last, two typical real cases are taken to test the applicability of the proposed model and the accuracy of the special GA. The optimal results indicate the mathematical model can lower the total investment and the corresponding GA can solve it efficiently. Show more

Keywords: Layout, pipeline network, GA, underground natural gas storage, MINLP

DOI: 10.3233/JIFS-191383

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-24, 2020

Authors: Chen, Tao | Lv, Hongxia | Sun, Yichen | Wang, Xiaoyi

Article Type: Research Article

Abstract: As one kind of highest hierarchy node on the network, the transfer scheme of high-speed railway hub timetable should be studied at priority. After defining the problem that optimizing transfer scheme of timetable at high-speed railway hub, this paper proposes time adjusting strategy and platform adjusting strategy to optimize the problem, of which the first strategy introduces a FUZZY set of reasonable time range to reduce the possible train conflicts at adjacent stations on the network, and the second strategy helps to use different transfer time to match the arrival and departure of trains. Then, an optimization model of timetable …based on passenger transfer is established with the minimized invalid transfer waiting time for passenger and train conflicts at adjacent stations as the objective function. The model is solved by the above two strategies in MATLAB software. Finally, the rationality and effectiveness of this model are verified, taking Shanghai Hongqiao Station as an example. Show more

Keywords: High-speed railway, hub, transfer, timetable optimization

DOI: 10.3233/JIFS-179662

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Li, Zhanhui | Fan, Jiancong | Ren, Yande | Tang, Leiyu

Article Type: Research Article

Abstract: As a common disease, migraine has a high incidence but the pathogenesis is still not clear. Resting-state Functional Magnetic Resonance Imaging (rs-fMRI) is an important research topic in the field of brain medicine, which can classify rs-fMRI data to automatically diagnose brain diseases. However, the original features of the rs-fMRI data are difficult to be extracted and the high-dimensional characteristics, which make the data analysis an extremely complicated task. Those have also plagued many researchers and bring great challenges to the existing pattern classification methods. Aiming at the high dimensionality of rs-fMRI data, in this paper, we propose a feature …extraction approach based on the combination of neighborhood rough set and PCA, thereby improving the accuracy of migraine identification. Firstly, Resting-State fMRI Data Analysis Toolkit plus was applied for preprocessing, calculating three characteristic indices: Amplitude of Low Frequency Fluctuation (ALFF), Regional Homogeneity (ReHo) and Functional Connectivity (FC. The inter-group difference analysis was performed by two-sample T test and GRF correction. Then, correlation coefficient matrix original features extraction was performed by means of automatic anatomical label template (AAL). Finally, the original features were trained by the traditional classification algorithm in machine learning. The experimental results show that the propose approach can obtain good performance in predicting migraine. Show more

Keywords: Resting state functional magnetic resonance imaging, migraine, correlation coefficient matrix, neighborhood rough set, principal component analysis, classification

DOI: 10.3233/JIFS-179661

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Nguyen, Luong V. | Thu, Nguyen T.

Article Type: Research Article

Abstract: In this paper, we prove a fixed point theorem for intuitionistic fuzzy mappings concerning F -contractions without using the Pompeiu – Hausdorff distance between cut sets of intuitionistic fuzzy mappings. This result and its consequences extend and generalize several results in the literature. An application to the existence for solutions of a delay integral equation of Volterra type and an example are given to illustrate the usability of our results.

Keywords: Intuitionistic fuzzy mappings, intuitionistic fuzzy fixed point, nonlinear F-contractions, delay integral equations

DOI: 10.3233/JIFS-191806

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Tingyu, Yang | Xiaoqian, Peng | Dingjun, Chen | Feiyu, Yang | Muneeb Abid, Malik

Article Type: Research Article

Abstract: With the increasingly close links between provinces and municipalities, the complexity and social connectivity of emergencies have gradually increased. How to realize the rapid and scientific dispatch of emergency resources based on the comprehensive transportation network has become a realistic need. However, due to barriers in management and communication between different administrative regions and different modes of transportation, emergency resource scheduling can only be carried out in the region, and the utilization of integrated traffic channels is insufficient to form a good multimodal transport system. The multi-agent system has strong self-organization ability, learning ability and reasoning ability, which solves problems …in the fields of dynamic decision-making and micro-simulation and provides ideas for solving the problem of comprehensive traffic emergency dispatching across regions. In this paper, the multi-agent system is introduced into the research of the task assignment problem of trans-regional comprehensive traffic emergency materials dispatching, based on the traditional bidding rules, the emergency dispatch task assignment rules are proposed and multi-agent trans-regional comprehensive traffic emergency dispatching model based on improved bidding rules is established. The simulation results show that the proposed method can break the regional barrier and form a multimodal transport scheme for emergency materials from the reserve point to the demand point under the minimum generalized time cost, providing decision support for emergency dispatch. Show more

Keywords: Multi-agent, trans-region, emergency dispatch, bidding

DOI: 10.3233/JIFS-179664

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Zhang, Peiwen | Tao, Zhifu | Liu, Jinpei | Jin, Feifei | Zhang, Junting

Article Type: Research Article

Abstract: The aim of this paper is to develop a multi-attribute group decision making (MAGDM) with picture fuzzy sets based on ELECTRE TRI method, i.e., an ELECTRE TRI based group decision making with picture fuzzy information is given. The MAGDM with picture fuzzy information based on picture fuzzy ELECTRE TRI outranking method is divided into three stages, i.e., the group decision information aggregation stage, determination of parameters and ELECTRE TRI outranking based outranking stage. A novel comparison law for picture fuzzy sets is introduced. In the group decision information aggregation stage, the concept of picture fuzzy normalized weighted Bonferroni mean (PFNWBM …) is developed. The developed decision procedure is further applied to the assessment of energy security. The numerical example shows that the developed group decision procedure is feasible and valid. Show more

Keywords: Multi-attribute group decision making, picture fuzzy sets, ELECTRE TRI, supplier selection, picture fuzzy normalized Bonferroni mean

DOI: 10.3233/JIFS-191540

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Liu, Yang | Lio, Waichon

Article Type: Research Article

Abstract: Nowadays, uncertainty theory has become a branch of axiomatic mathematics and has been studied by many researchers. In particular, uncertainty distribution is one of the most important tools to deal with indeterminate quantity in uncertainty theory. Peng and Iwamura (2010) presented a sufficient and necessary condition of a function being an uncertainty distribution. This paper gives a counterexample to illustrate this condition is not appropriate. A revision of the sufficient and necessary condition is also provided in this paper.

Keywords: Uncertainty theory, uncertain variable, uncertainty distribution

DOI: 10.3233/JIFS-191535

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Xu, Changan | Li, Sihan | Xu, Heying | Ni, Shaoquan

Article Type: Research Article

Abstract: Passenger train occupation rate directly affects Railway Company’s revenue and capacity utilization of railway infrastructure, and measures to improve passenger train occupation rate is always the focus of railway companies’ attention. However, researches on what, and how factors influence passenger train occupation rate remain sparse. Based on the collective data of 363 passenger trains on the Beijing-Shanghai High-speed Railway in November 2015, this paper establishes a data-driven analysis framework to explore the influencing factors of passenger train occupation rate. Specifically, we first analyze the possible factors that influence train occupation rate from the perspective of train service planning. Then, the …approach of association rules is applied to analyze the potential relationship between train occupation rate and its influencing factors. And a total of 6711 and 8133 association rules were generated for high and low train occupation rate of passenger trains, respectively. Further analysis found that train departure and arrival times, train departure and arrival station class and the type of trains are the main factors influencing the level of train occupation rate. These findings can provide reference for train service planning. Show more

Keywords: Passenger train occupation rate, association rules, train service planning, Beijing-Shanghai high-speed railway

DOI: 10.3233/JIFS-179663

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Xie, Chao-Fan | Xu, Lu-Xiong | Zhang, Fuquan

Article Type: Research Article

Abstract: Because of high efficiency and cleanness, the simulated moving bed (SMB) is the most important technology in chromatographic separation. SMB system, which contains several sectors of flow rate, the switching time of valves and many other possible influencing variables, is complex, highly sensitive and difficult to control. This paper proposes adjusted fuzzy control; the adjusted fuzzy controller is applied to the SMB system to control the separation concentration by establishing a variable direction correction formula. Compared with the traditional fuzzy controller, the adjusted fuzzy controller does not need to analyze the dynamic direction of the control force in advance, moreover, …the control accuracy is high and the fluctuation is small for SMB system. Show more

Keywords: Chromatographic, SMB, fuzzy, control

DOI: 10.3233/JIFS-179660

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Meng, Zhenyu | Yang, Cheng | Meng, Fanjia | Chen, Yuxin | Lin, Fang

Article Type: Research Article

Abstract:  Differential Evolution (DE) was an easy-coding and efficient stochastic algorithm for global optimization, and the whole optimization process simulates biological evolution. Superior individuals of the population that were suitable for the environment were retained during the evolution, and consequently the tolerable solutions could be obtained in the end. Despite the excellent performance of DE algorithm, there were still some shortcomings. For example, the general performance of DE depended largely on mutation strategy and control parameters, how to design the appropriate control parameters and mutation strategy were difficult tasks. Here a novel DE variant was proposed to overcome these shortcomings. By …incorporating the depth information of previous generations of populations, a better diversity of trial vector candidates could be secured during the evolution process. Moreover, the thought that successful parameters should be retained to guide the update of themselves during the evolution was also incorporated into the novel algorithm. The optimization performance of the new proposed DE variant was verified under CEC 2013 test suit containing 28 benchmarks, and the results showed its competitiveness with several state-of-the-art DE variants. Show more

Keywords: Differential evolution, depth information, global optimization, real-parameter optimization

DOI: 10.3233/JIFS-179655

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Zhang, Yun | Zhang, Yude | He, Wei | Yu, Shujuan | Zhao, Shengmei

Article Type: Research Article

Abstract:  Feature selection is an essential part in the data preprocessing. In the text classification, most of the previous feature selection algorithms rarely consider the redundancy between features. This paper focuses on eliminating redundancy. After modifying the formula of feature correlation of original fast correlation-based filter (FCBF) and updating the algorithm strategy, we propose a new approach named improved feature size customized fast correlation-based filter (IFSC-FCBF). In addition, we combine IFSC-FCBF with Naive Bayes (NB) classifier for text classification, and test it in four typical text corpus data sets. The results demonstrate that with the same feature size, IFSC-FCBF method has …the advantages of higher accuracy and shorter running time than other methods. Show more

Keywords: Feature selection, Naive Bayes, text classification, FCBF, IFSC-FCBF

DOI: 10.3233/JIFS-191066

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Bahrani, Payam | Minaei-Bidgoli, Behrouz | Parvin, Hamid | Mirzarezaee, Mitra | Keshavarz, Ahmad | Alinejad-Rokny, Hamid

Article Type: Research Article

Abstract: Recommender Systems (RS ) are expected to suggest the accurate goods to the consumers. Cold start is the most important challenge for RSs. Recent hybrid RS s combine ConF and ColF . We introduce an ontological hybrid RS where the ontology has been employed in its ConF part while improving the ontology structure by its ColF part. In this paper, a new hybrid approach is proposed based on the combination of demographic similarity and cosine similarity between users in order to solve the cold start problem of new user type. Also, a new approach is proposed based …on the combination of ontological similarity and cosine similarity between items in order to solve the cold start problem of new item type. The main idea of the proposed method is to expand user/item profiles based on different strategies to build higher-performing profiles for users/items. The proposed method has been evaluated on a real dataset and the experimentations indicate the proposed method has the better performance comparing with the state of the art RS methods, especially in the case of the cold start. Show more

Keywords: Recommender system, hybrid recommender system, ontology, profile expansion, KNN

DOI: 10.3233/JIFS-191225

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Chu, Shu-Chuan | Chen, Yuxin | Meng, Fanjia | Yang, Chen | Pan, Jeng-Shyang | Meng, Zhenyu

Article Type: Research Article

Abstract:  Optimization demands exist everywhere in the real world especially in science studies and engineering practices, and it is important that the method to deal with intricacy optimization problems should itself be relative simple. Particle Swarm Optimization (PSO) and Differential Evolution (DE) both are simple evolutionary algorithms (EAs) which are proposed for single-objective optimization and both of them have been proved to be efficient methods for optimizing applications, however, there are still some weakness existing within them. A innovative evolutionary method named QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm which is derived from, also tackles some weaknesses of PSO and DE algorithm, and …obtains better performance on commonly used test suites. The key characteristic of QUATRE is that an automatically generated matrix named evolution matrix M is implemented in evolutionary process, which is taken as an alternative of employing the crossover rate CR . Here in this paper, we present a novel QUATRE variant, named IS-QUATRE, which can explore the search area in a better way comparison with the previous method, and relatively good optimization ability can be obtained by our proposed IS-QUATRE algorithm under CEC2013 test suit. And the conducted experimental results validate that our proposed IS-QUATRE is competitive with some other famous PSO and DE variants. Show more

Keywords: Internal search, QUATRE, single-objective optimization, stochastic optimization, real-parameter optimization

DOI: 10.3233/JIFS-179656

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Zhang, Jinxin | Li, Hui | Zhang, Xiufang | Yu, Hua | Liang, Fengna | Qin, Zijun | Jiang, Miaohua

Article Type: Research Article

Abstract: Soil erosion is one of the main environmental problems in the world, and also an important branch of natural environment protection. Taking Minjiang River Basin as the research area, based on the supervised classification of land use status map, the comprehensive soil erosion modulus map was generated by referring to the soil erosion evaluation index and the revised soil loss equation (RUSLE). The results showed that the Minjiang River Basin is dominated by mild eroded area and moderate eroded area, accounting for 41.50% and 54.81% of the total area respectively. High eroded area accounted for only 3.69%, mainly in the …north and west, and there was no extremely sensitive area. The intensity of soil erosion of each land use type was unused land > garden land > cultivated land > forest land > water body > construction land. Through the discussion of the sensitivity evaluation of soil erosion in Minjiang River Basin, it can provide some references for the relevant departments to the soil and water conservation work in Minjiang River Basin. Show more

Keywords: Soil erosion, sensitivity assessment, Minjiang River Basin, land use

DOI: 10.3233/JIFS-179658

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Zhang, Fuquan | Wang, Yiou | Wu, Chensheng

Article Type: Research Article

Abstract:  Digital creativity is creative expression derived from cultural creativity and information technology. In order to overcome the problem in the creative generation in the condition of fuzzy and uncertain ideas, an automatic generation method of cross-modal fuzzy creativity (AGMCFC) is proposed. In this subject, fuzzy creative data sets and learning retrieval network are constructed for the sake of extracting original creative data effectively. And the logical correlations between creative objects are acquired dynamically based on the graph neural network. Creative objects and creative styles are generated by using generative adversarial nets technology and style transfer technology, respectively. Then, the projectiles, …boundary markers and location words of the creative scene objects are generated by analyzing related attributes of each entity. After adjusting the layout, creative works are automatically generated. A fuzzy creative generating environment is implemented. Experimental results show that the screened number of AGMCFC method is about twice as much as that of manual method, and the accuracy rate of AGMCFC method is improved compared with the manual method. AGMCFC method performs well at creative generation of fuzzy ideas automatically. Show more

Keywords: Generation of fuzzy creativity, cross-modal, graph neural network, creative works

DOI: 10.3233/JIFS-179657

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Temucin, Tolga | Tuzkaya, Gulfem

Article Type: Research Article

Abstract: Reverse logistics has become one of the emerging research and application areas since the early 1990 s due to several driving forces such as economic benefits, governmental regulations, increasing levels of environmental problems, etc. As an essential part of reverse logistics (RL) literature, Reverse Logistics Network Design (RLND) efforts can provide economic and ecological advantages to the supply chains. In this study, we consider a reverse distribution channel and try to determine the locations of the collection centers (CCs) and repair centers (RCs) and the amount of product flow between the customers-CCs and CCs-RCs. Considering the multi-objective nature of the RLND …problems, total cost and total delay minimization and total average capacity utilization maximization objectives are taken into account. This problem is formulated as a multi-objective mixed integer nonlinear programming model and is solved by two approaches: a heuristic and a tabu search based meta-heuristic in which both of the solution approaches are integrated with weighted max-min approach. Numerical analyses have been carried out to show the effectiveness of the proposed approaches and the solutions obtained from each approach have been compared. Show more

Keywords: Reverse logistics, network design, tabu search, weighted max-min method

DOI: 10.3233/JIFS-190431

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2020

Authors: Flores-Sosa, Martha | Avilés-Ochoa, Ezequiel | Merigó, José M.

Article Type: Research Article

Abstract: The induced ordered weighted average (IOWA) is an aggregation operator that provides a parameterized family of operators between the minimum and the maximum. This work presents a new application that uses the simple linear regression (LR) and the IOWA operator in the same formulation. We study some of its main properties and particular cases. The main advantage of the linear regression IOWA operator is that it unifies the IOWA operator with the linear regression in the same formulation considering the degree of optimism and pessimism of the decision maker. Thus, we can under- or over- estimate the regression according to …complex attitudes that the decision may have in the analysis. The work ends analyzing the applicability of this new approach in a problem regarding exchange rate forecasting. The objective of the new approach is to analyze the information in a more complete way. Show more

Keywords: IOWA operator, linear regression, aggregation operator

DOI: 10.3233/JIFS-179642

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Almarashi, Abdullah M. | Algarni, Ali | Abdel-Khalek, S. | Khalil, E.M.

Article Type: Research Article

Abstract:  In this article we estimate the nonlocal correlation between a two qubits and OF (optical field) initially started in the even deformed binomial distribution (EDBS). Explicit forms of the EDBS as the initial states of the RF are presented. We investigate the dynamical and statistical properties of the linear entropy as a quantifier of the correlation and purity of the proposed system. Also, the correlation between the two qubits is quantified by the negativity. Some statistical estimations of the RF are investigated by of Mandel parameter and compared by the two types of correlation The relation between the qubit inversion, …two qubits-RF nonlocal correlation, negativity and Mandel parameter is obtained. The effective of Stark shift on the dynamical operators for the RF distribution is examined. The results are shown the a high amount of field-qubit nonlocal is reached for a high value of deformation parameter. Also, the statistical properties of the field is Poissonian or sub-Poissonian photon distribution. Show more

Keywords: Even deformed binomial distribution, mandel parameter, negativity, nonlocal correlation

DOI: 10.3233/JIFS-179559

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Hsiao, Shou-Ching | Liu, Zi-Yuan | Tso, Raylin | Kao, Da-Yu | Chen, Chien-Ming

Article Type: Research Article

Abstract: Gated Recurrent Unit (GRU) has wide application fields, such as sentiment analysis, speech recognition, and other sequential data processing. For efficient prediction, a growing number of model owners choose to deploy the trained GRU models through the machine-learning-as-a-service method (MLaaS). However, deploying a GRU model in cloud generates privacy issues for both model owners and prediction clients. This paper presents the architecture of PrivGRU and designs the privacy-preserving protocols to complete the secure inference. The protocols include base protocols and principal protocols. Base protocols define basic linear and non-linear computations, while principal protocols construct the gating mechanisms of GRUs. The …main benefit of PrivGRU is to address privacy problems while enjoying the efficiency and convenience of MLaaS. The overall secure inference is performed on shares, which retain two properties of security: correctness and privacy. To prove the security, this work adopts Universal Composability (UC) framework with the honest-but-curious corruption model. As each protocol is proved to UC-realize the ideal functionality, it can be arbitrarily composed in any manner. This strong security feature makes PrivGRU more flexible and practical in future implementation. Show more

Keywords: Privacy-preserving, MLaaS, gated recurrent unit, additive secret sharing, UC framework

DOI: 10.3233/JIFS-179652

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Liu, Wei | Mao, Yu | Ci, Linlin | Zhang, Fuquan

Article Type: Research Article

Abstract:  It is not foolproof for intrusion detection to focus only on the network level and the program level. Internal security and external security of information systems should be given equal attention. User-level intrusion detection can deter and curtail attackers from damaging information systems. Even if the mimic attacker has gained and enhanced the host user privileges that he illegally obtained. In this paper, a novel method based on recurrent neural networks (RNNs) is used to predict user command sequences and prophesy user behaviors. The experimental results show that our command sequence-to-sequence model is robust and effective for solving long sequential …problem on three different data sets including Purdue University data set, SEA data set and self-collected data set. Show more

Keywords: User behavior, recurrent neural networks, anomaly intrusion detection, attacks and defenses

DOI: 10.3233/JIFS-179659

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Liu, Mingtang | Wang, Li | Qin, Zening | Liu, Jiaqi | Chen, Jian | Liu, Xuemei

Article Type: Research Article

Abstract: In order to make the feature data more linearly separable for support vector machine(SVM) classifier, a set of different scale and direction parameter was proposed for improving the recognition effect of cement slope damage in high fill channels. The Gabor wavelet was used to extract the multi-scale and multi-directional features of the high-fill channel’s abrupt features. Then SVM algorithm was utilized to perform damage classification and level recognition. To compare the recognition effect of the Gabor-SVM method, histogram-SVM, grayscale symbiotic matrix -SVM, canny-SVM algorithm were adopted to identify the damage degree of cement surface in the same environment, and these …damage recognition rates are compared with Gabor-SVM’s. The experimental results show that the damage recognition model, based on Gabor-SVM, tends to better stable value when the wavelet takes 6 scale and 12 directions. The recognition rate of the normal slope is 0.98, while the recognition rate of the crack, hole, and broken slope are 0.63, 0.88 and 0.90, respectively. Overall, the damage recognition model, based on Gabor-SVM, has better recognition effect, and it will provide technical support for finding potential leakage hazards in the high fill channel of South-to-North Water Diversion Project. Show more

Keywords: Key words: Middle route of South-to-North Water Diversion Project, Feature extraction of multiple scales and directions, damage recognition, Gabor wavelet, support vector machine

DOI: 10.3233/JIFS-190767

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Zhaoyan, Hu | Yonglong, Luo | Xiaoyao, Zheng | Yannian, Zhao

Article Type: Research Article

Abstract:  With the popularity of networks and the increasing number of online users, recommender systems have suffered from the privacy leakage of sensitive information. While people enjoy recommender services, their information is exposed to the networks. To protect the privacy of users when using the recommender services, we propose a multi-level combined privacy-preserving model that maintains high accuracy of recommendation with privacy protection and alleviates the data sparsity problem. Our scheme contains two steps of recommendation. First, a multi-level combined random perturbation (MCRP) model is proposed on the client side. Our model dynamically divides multiple disturbance levels and adds noise of …different ranges to the rating matrix according to Gaussian and uniform mixed disturbances. Second, on the server side, we propose a pseudo rating prediction filling (PRPF) algorithm based on the matrix factorization model. Combining the PRPF algorithm with the MCRP method significantly improves the recommender accuracy and effectively increases privacy security. Sensitive analysis and comparison experiments show that the proposed privacy method has certain advantages in security and recommender accuracy by using three publicly available datasets. Show more

Keywords: Recommender system, matrix factorization, privacy protection, random perturbation, sparse data

DOI: 10.3233/JIFS-191287

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Vinh An, Truong | Van Hoa, Ngo

Article Type: Research Article

Abstract:  In this work, we consider a new form of fuzzy fractional Volterra integral equations (FFVIEs) involving the generalized kernel functions. By using the monotone iterative technique (MIT) combined with the method of lower and upper solutions, the existence of extremal solutions of FFVIEs is established. Some examples are given to illustrate our main results.

Keywords: Fuzzy fractional integral equations, generalized kernel functions, extremal solutions, monotone iterative technique

DOI: 10.3233/JIFS-191746

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Xue, Z.-A. | Zhao, Li-Ping | Zhang, Min | Sun, Bing-Xin

Article Type: Research Article

Abstract: Three-way decisions have become a representative of the models dealing with decision-making problems with uncertainty and fuzziness. However, most of the current models are single granular structures that cannot meet the needs of complex fuzzy environmental decision-making. Multi-granulation rough sets can better deal with fuzzy problems of multiple granularity structures. Therefore, three-way decisions will be a more reasonable decision-making model to address uncertain decision problems in the context of multiple granularity structures. In this paper, firstly we propose the four different conditional probabilities based on support intuitionistic fuzzy sets, which are referred to as support intuitionistic fuzzy probability. Then, a …multi-granulation support intuitionistic fuzzy probabilistic approximation space is defined. Secondly, we calculate the thresholds α and β by the Bayesian theory, and construct four different types of multi-granulation support intuitionistic fuzzy probabilistic rough sets models in multi-granulation support intuitionistic fuzzy probabilistic approximation space. Moreover, some properties of lower and upper approximation operators of these models are discussed. Thirdly, by combining these proposed models with three-way decision theory, the corresponding three-way decision models are constructed and three-way decision rules are derived. Finally, an example of person-job fit procedure is given to prove and compare the validity of these proposed models. Show more

Keywords: Support intuitionistic fuzzy sets, rough sets, support intuitionistic fuzzy probabilistic, multi-granulation rough sets, three-way decisions

DOI: 10.3233/JIFS-191657

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2020

Authors: Vinh An, Truong | Van Hoa, Ngo

Article Type: Research Article

Abstract: In this work, a new class of generalized fractional integral equations involving the kernel ψ -function in the fuzzy setting is introduced. With this problem, we can recover a wide class of fractional fuzzy integral equations by choosing the kernel ψ -function. In this sense, we provide sufficient conditions for the existence, uniqueness of solutions and δ -Ulam-Hyers-Rassias stability of the given problems. Some examples are given to illustrate our main results.

Keywords: δ-Ulam-Hyers-Rassias, kernel ψ-functions, Fuzzy fractional integral equations

DOI: 10.3233/JIFS-191743

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Wu, Mu-En | Lin, Sheng-Hao | Wang, Jia-Ching

Article Type: Research Article

Abstract: The objective in using the Kelly criterion for money management is to maximize returns; however, in many cases, the risk level exceeds that which the investor can bear. In this study, we present an algorithm to calculate the bidding fraction, while taking into account the level of risk (i.e., the maximum drawdown). The proposed algorithm is based on ensemble learning with a combination of bagging and subset resampling. Our assessment results obtained using the FF48 (i.e., Fama-French-48) dataset revealed that when the maximum drawdown was 5% and 10%, ensemble learning outperformed the conventional approach by 2% and 4%, respectively.

Keywords: Kelly criterion, ensemble learning, Monte Carlo simulation, money managemen

DOI: 10.3233/JIFS-179654

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Qu, Junsuo | Qiao, Ning | Shi, Haonan | Su, Chang | Razi, Abolfazl

Article Type: Research Article

Abstract: In this paper, we designed a smart bracelet to realize human behavior recognition, remote monitoring, fall detection, alarm and other functions. We use a six-axis inertial measurement module to collect a large amount of human body posture data. The Kalman filter is used to preprocess the data of acceleration and gyroscope, and then the processed series data is segmented by sliding window method. At last these data are put into a convolutional neural network(CNN) to identify human activities. Furthermore, we designed a two-level fall behavior judgment, the first-level threshold determination is performed through smart bracelet, when a suspected fall behavior …occurred, the sequence data are uploaded to the cloud platform, the second CNN discriminant model is triggered to accurately determine whether a fall behavior occurs. Show more

Keywords: Convolutional neural network, human behavior recognition, fall detection

DOI: 10.3233/JIFS-179651

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Xue, Xingsi | Wu, Xiaojing

Article Type: Research Article

Abstract:  Biomedical ontology matching dedicates to find two heterogeneous ontologies’ alignment and address their heterogeneity problem. Typically, a biomedical ontology has various biomedical concepts that are described with various labels and datatype property names, which forms a lexical space where each label or datatype property represents one dimension. Therefore, it is an effective way to present two biomedical concepts in a vector space, and use the cosine distance to measure their similarity. In this work, we present two biomedical concepts in a lexical vector space which is constructed with their inner and context concepts’ lexical information, and then utilize two vector’s …cosine distance to measure similarity value. Then, we propose a compact Evolutionary Algorithm (cEA) to find the concept correspondences. The experiment uses Ontology Alignment Evaluation Initiative (OAEI)’s testing cases, and the expeirmental results with Vector space Based Ontology Matcher (VBOM), Genetic Algorithm based Ontology Matcher (GAOM) and OAEI’s participants show the effectiveness of our proposal. Show more

Keywords: Biomedical ontology matching, lexical vector space, compact evolutionary algorithm

DOI: 10.3233/JIFS-179650

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2020

Authors: Li, Jingmei | Wu, Weifei | Xue, Di

Article Type: Research Article

Abstract:  Transfer learning is a new machine learning algorithm. It solves problems in different but related target domains by utilizing the knowledge in existing data. Based on the classical SVM algorithm and transfer learning, a selective transfer learning support vector machine (STL-SVM) algorithm is proposed in this paper. First, STL-SVM uses the maximum mean discrepancy to measure the weight vector of the source domain samples relative to the target domain, and selects samples from the source domain according to each weight to avoid negative transfer. Then, the knowledge in the source domain is learned by the approximate extreme point support vector …at the minimum training data cost. Finally, the object function is constructed by the obtained knowledge and the soft-margin SVM. In the constraint conditions of the objective function, the learned knowledge that is highly correlated with the target domain is selected, and further, the phenomenon of negative transfer is avoided in principle. STL-SVM solves the problem of negative transfer, and has considerable advantages in training time efficiency compared with the existing algorithms. The experimental results on artificial and real datasets show the effectiveness of the proposed algorithm. Show more

Keywords: Machine learning, support vector machine, transfer learning, classification

DOI: 10.3233/JIFS-190055

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2020

Authors: Wang, Xingang | Wang, Ke

Article Type: Research Article

Abstract: In many cases, complex problems cannot be accurately described by precise numerical values. Fuzzy theory provides a suitable tool for solving these problems. However, if decision makers cannot reach an agreement on the method for defining linguistic variables based on fuzzy sets, TIVFNs (triangular interval-valued fuzzy numbers) can provide more accurate modeling. Therefore, solving fuzzy MCGDM (multiple criteria group decision-making) problem with an unknown expert weight and criterion weight in TIVFNs has become an important research direction. In this paper, TIVF-VIKOR (triangular interval-valued fuzzy VIKOR) method, which is suitable for the environment of TIVFNs, is proposed to solve the problem …of fuzzy MCGDM. To achieve this goal, the TIVF-VIKOR method is innovatively adopted similarity and coefficient of variation are combined to calculate expert weight, and deviation maximization method based on divergence matrix is used to calculate criterion weight. VIKOR method is used to find the compromise solutions, which are converted into the form of binary connection number, and the optimal compromise solution is obtained after ranking. The proposed method is applied to the problem of machine fault detection, and the validity and feasibility of the method are illustrated. Compared with the TOPSIS∖ELECTRE method, the ranking results of the three methods are equivalent, and the fluctuation of the TIVF-VIKOR method is more distinct. Show more

Keywords: Triangular interval-valued fuzzy numbers, multiple criteria group decision-making, binary connection number, VIKOR method

DOI: 10.3233/JIFS-191261

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Liu, Yan | Wang, Xiao-Kang | Wang, Jian-Qiang | Li, Lin | Cheng, Peng-Fei

Article Type: Research Article

Abstract: This paper proposes a cloud model-based Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) method with 2D uncertain linguistic variables (2DULVs). 2DULVs are adopted by decision makers (DMs) to evaluate each alternative under the criteria because they can provide extra evaluation information. Cloud model is adopted to depict randomness and fuzziness. The possibility degree and possibility degree index are defined to develop an improved PROMETHEE II method for sorting alternatives. Entropy weight method is used to calculate the weight of each criterion. A renewable energy performance sample is used to illustrate the applicability of the proposed method. Sensitivity analysis and …four comparative experiments demonstrate the stability and accuracy of the proposed approach. Show more

Keywords: 2D uncertain linguistic variable, cloud, possibility degree, possibility degree index, improved PROMETHEE

DOI: 10.3233/JIFS-191546

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2020

Authors: Khater, Mostafa M.A. | Attia, Raghda A.M. | Qin, Haiyong | Kadry, Heba | Kharabsheh, R. | Lu, Dianchen

Article Type: Research Article

Abstract:  This research paper investigates the stable computational, semi-analytical, and numerical solutions of the nonlinear complex fractional generalized–Zakharov system. This system describes the nonlinear interactions between the low-frequency, acoustic waves and high-frequency, electromagnetic waves. The modified Khater method is applied to find the analytical solutions then the stability property of these solutions is discussed by using the Hamiltonian system properties. Moreover, stable computational solutions are used as the initial condition in the semi-analytical and numerical schemes. The Adomian decomposition and septic B–spline schemes are used to find the semi-analytical and numerical. For more explanation of the obtained analytical solutions, some sketched …are plotted in different types. Also, the comparison between the distinct types of obtained solutions is shown by calculating the absolute value of error. The performance of the used method explains the powerful, effective, and the ability for applying to different forms of nonlinear evolution equation. Show more

Keywords: The nonlinear complex fractional generalized–Zakharov system, modified Khater method, Adomian decomposition method, Septic B–spline scheme, computational, semi-analytical, and numerical solutions

DOI: 10.3233/JIFS-179569

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Shang, Bo | Huang, Taozhen | Du, Xingyu

Article Type: Research Article

Abstract: In a significant period of Chinese energy reformation to the point of expediting revolution in energy production and consumption, and promoting green low-carbon upgrading transformation of energy electricity, Chinese government has to implement the obligatory policy of renewable portfolio standards (RPS) with specific institutional provisions sternly. The renewable energy quotas in thermal power industry with carbon emission abatement constraints particularly have a latent impact on the behavior of thermal electricity producers, which is ineluctably involved in electricity connection of grid companies. To make clear the positive role in boosting investment in renewable energy generation in thermal power industry under mandatory …quotas requirements, we will utilize evolutionary game based on system dynamics (SD) to tackle with the sophisticated nexus among the government, thermal power producers and grid companies. We begin analysis of general evolutionary strategy stability in scenario ll by dynamically adjusting values of external variables of SD model to uncover pivotal variables affecting evolutionary strategy stability. Then in scenario I, the dynamic punishment structure consisting of cost elements to spark off the emulation of optimal manoeuvre selections of tripartite game agents is amended based on the simulation of vital variables affecting evolutionary strategy stability in scenario II. The significant conclusions provide decision-making support and management enlightenment for Chinese government to edge renewable energy generation capacity of thermal power producers and constrained degree of dynamic penalty for grid companies. Show more

Keywords: Renewable portfolio standards (RPS), China’s power market, Carbon abatement, Government regulation, evolutionary strategy stability, system dynamics

DOI: 10.3233/JIFS-191470

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-29, 2020

Authors: Mishra, Amit Kumar | Joshi, Nisheeth | Mathur, Iti

Article Type: Research Article

Abstract: Analysis of the terrorist network is a process to analyze or deriving Useful information from the available network data. Ranking The Terrorist nodes within a terrorist network in identifying the most influential node is essential for the elaboration of Covert network mining. The purpose of this paper is to implement an approach of two dimensional criteria weight determination along with logarithmic concept implementation for vital node investigation in term of their influential ability. Betweenness, Closeness, Eigenvector, Hub, In-degree, Inverse closeness, Out-degree and Total degree considered as criteria and terrorist involved in 9/11 terrorist attack considered as alternatives used to formulate …a decision problem. Although an integrated approach of Fuzzy based subjective-Aggregation concept based objective criteria weight determination and Ranking alternatives by the implementation of the logarithmic concept is used to solve multi criteria decision problems in order to show the application of most centralized node identification process which can be obtained easily by classification and selection problem solution using multiple criteria and alternatives. Show more

Keywords: Social network, Social Network Analysis(SNA), Terrorist network analysis(TNS), Fuzzy based criteria weight, Aggregation criteria weighting, Approach of logarithmic concept(APLOCO), Multi Criteria Decision Making(MCDN), Centrality measures, Most influential node

DOI: 10.3233/JIFS-191899

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: He, Sang-Sang | Wang, Yi-Ting | Wang, Jian-Qiang | Cheng, Peng-Fei | Li, Lin

Article Type: Research Article

Abstract: Failure mode and effect analysis is a powerful risk analysis tool in engineering management. When properly conducted, FMEA can make a huge contribution to reduce costs. The traditional FMEA ranks the failure modes on the basis of Risk Priority Number, which is defined as the multiplication of three risk factors. However, this method has always been criticized for it can’t handle the situation where the information given is uncertain or ambiguous. In order to extend the application of FMEA under the fuzzy environment, in this paper, we proposed a novel risk assessment model known as probabilistic linguistic ELECTRE II method …to rank failure modes based on FMEA. To realize this goal, probabilistic linguistic term sets (PLTSs) that consider both the hesitant information and probabilistic information are introduced to depict decision maker’s cognitive information. To better use the PLTSs in the decision-making process, some important information measures are defined, and a method to obtain the combined weight based on entropy weight of PLTSs is also proposed. Subsequently, we establish a score-deviation based PLTS-ELECTRE II model to study FMEA as a multi-criteria group decision-making problem. Finally, we successfully apply this model in a nuclear reheat valve system and the effectiveness of the proposed method is verified by sensitivity analysis and comparative analysis. Show more

Keywords: Risk management, outranking, probabilistic linguistic term set, combined weight, hybrid distance measure

DOI: 10.3233/JIFS-191398

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Yang, Yu | Wang, Jian-Qiang | Wang, Jing

Article Type: Research Article

Abstract: In this study, a multi-criteria group decision making (MCGDM) framework is constructed for electric vehicle fast-charging station (EVFCS) selection using a proportional hesitant fuzzy set (PHFS) that can describe two aspects of information: the possible membership degrees in the hesitant fuzzy elements and associated proportion representing statistical information from different groups. A newly extended distance measure for PHFSs is introduced and an extended maximizing deviation method is constructed to obtain criteria weights objectively. Accordingly, an integrated PHFS-VIKOR (VlseKriterijum-ska Optimizacija I Kompromisno Resenje) method embedded with a new distance measure and extended maximizing deviation method is presented. With increasing concerns about …range anxiety, it is essential to seek an optimal location for EVFCS considering efficient utilization of resources and long-term development of socio-economy under proportional hesitant fuzzy environment. Lastly, an illustration with sensitivity analysis and comparative analyses is provided to demonstrate the validity and robustness of our proposal. Show more

Keywords: Multi-criteria group decision making, proportional hesitant fuzzy set, distance measure, VIKOR, maximizing deviation method

DOI: 10.3233/JIFS-190156

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2020

Authors: Mauleón-Méndez, Emilio | Genovart-Balaguer, Juanabel | Martorell-Cunill, Onofre | Mulet-Forteza, Carles

Article Type: Research Article

Abstract: This paper aims to present a current overview of the main productive and influential countries around the world in the tourism, leisure and hospitality field. The methodology includes a bibliometric analysis in all research journals that are indexed in the Web of Science in the tourism, leisure and hospitality field in 2014 respect to the national contribution that these countries made in these journals. The study shows that USA is the country leadership in the tourism, leisure and hospitality research. Other countries, such as UK and People’s Republic of China, also get a main position in the ranking. There are …not previous studies examining all the journals indexed in the Web of Science in the tourism, leisure and hospitality field during a period as wide as this one nor including as many countries as those analyzed in this paper (Top 50). Show more

Keywords: Bibliometric analysis, web of science, country, journals, research productivity, tourism

DOI: 10.3233/JIFS-179647

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Villa-Monte, Augusto | Lanzarini, Laura | Corvi, Julieta | Bariviera, Aurelio F.

Article Type: Research Article

Abstract:  Currently, each person produces 1.7MB of information every second in different formats. However, the vast majority of information is text. This has increased the interest to study techniques to automate the identification of the relevant portions of text documents in order to offer as a result an automatic summary. This article presents a technique to extract the most representative sentences of a document taking into account by the user’s criteria. These criteria are learned using a neural network, from a minimum set of documents whose sentences have been rated by the user in terms of importance. To verify the performance …of the proposed methodology, we used 220 scientific articles from the PLOS Medicine journal published between 2004 and 2016. The results obtained have been very satisfactory. Show more

Keywords: Text summarization, extractive summaries, sentence scoring, feature selection, neural networks

DOI: 10.3233/JIFS-179648

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Shahzadi, Gulfam | Akram, Muhammad | Davvaz, Bijan

Article Type: Research Article

Abstract:  A Pythagorean fuzzy soft set, an extension of intuitionistic fuzzy soft set, plays an essential role to handle the vagueness in many real-life problems. We apply this concept to graph theory, and present certain new notions including, perfectly regular Pythagorean fuzzy soft graphs (PFSGs), perfectly edge-regular PFSGs and explore some of their properties. We formulate the notion of perfectly irregular PFSGs, perfectly edge-irregular PFSGs and open neighborhood degree sum ( O ˆ NDS ) and closed neighborhood degree sum ( C ˆ NDS ) of PFSGs. …Finally, we discuss some decision-making problems of PFSGs. Show more

Keywords: Pythagorean fuzzy soft graphs, perfectly edge-regular, perfectly edge-irregular

DOI: 10.3233/JIFS-191610

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Mohanta, Kartick | Dey, Arindam | Pal, Anita | Long, Hoang Viet | Son, Le Hoang

Article Type: Research Article

Abstract:  Information in many real life problems collect from multi agents, i.e., "multipolar information" exists. This multipolar information cannot be properly modeled by m - polar fuzzy graph or intutionistic fuzzy graph. An m -polar neutrosophic model is very much efficient for such real word problems which can construct more precise, flexible, and comparable system as compared to the classical, fuzzy and neutrosophic graph models. In this paper, we present the definition of m -polar neutrosophic graph model. Some new operations, such as union, join, composition and ring sum of two m -polar neutrosophic graph are defined here. We define six …new products on m -polar neutrosophic graphs namely strong product, semi strong product, complete product, direct product, cartesian product and lexicographic product. Some idea of complement, isomorphism, weak and co weak isomorphism on m -polar neutrosophic graph are introduced here. We also present several associated properties and theorems of m -polar neutrosophic graph. We introduce a model of m -polar neutrosophic graph, which is applied in evaluating the teacher’s performance of a college. The performances of the teachers are computed based on the response score (feedback) of the students of the college. We also present a numerical example to illustrate our proposed model. Show more

Keywords: Multipolar information, neutrosophic set, m-polar neutrosophic graph, union, direct product

DOI: 10.3233/JIFS-191520

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2020

Authors: Pineda-Escobar, Maria Alejandra | Merigó Lindahl, José M.

Article Type: Research Article

Abstract: The concept of the Base/Bottom of the pyramid (BoP), since its first use in the early 2000 s, has been used by researchers and practitioners alike. The past 16 years has witnessed a significant increase in output of published research on the subject. This study aims to analyze the main contributions in this field, using a bibliometric approach. It considers key bibliometric indicators, such as leading authors, journals, institutions, sources, countries, and the most common keywords. A graphical visualization in bibliometric maps has also been developed, using the VOSviewer software. As expected, the results indicate a sharp increase in BoP research …over the last 5 years. The most influential research is from the USA, although there has been a considerable wave of production from the global south. The results may be of interest for those hoping to gain an overview of the current state of BoP research. Show more

Keywords: Base of the Pyramid, Bottom of the Pyramid, BoP, bibliometrics, business research, VOS viewer

DOI: 10.3233/JIFS-179645

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Ghasemzadeh, Mehdi | Hadidi, Khayrollah

Article Type: Research Article

Abstract: In this paper, the design and simulation results of a general-purpose fuzzy logic controller (FLC) with mixed-signal (analog and digital) inputs and digital outputs are presented. Based on a new strategy, it provides simplicity and high speed from the analog prospective and a total digital system advantages with unchanged digital system properties. A novel and reliable structure with respect to other topologies for the fuzzifier section is designed which enhances the accuracy and the velocity. In order to detect minimum and maximum of the input currents at the same time, an inference engine consisting of a min & max circuit …is an addition. The benchmark for the defuzzifier in the proposed design is simplicity and through a simple approach, the center of area (COA) is attributed to the defuzzifier. The proposed controller circuit consists of two inputs, sixteen rules and one output designed in 0.35μ m CMOS standard technology and simulated with MATLAB systematically. The total controller circuit is simulated with HSPICE simulator (BSIM3v3 parameters) and the layouts were extracted with Cadence Virtuoso v 5.1. The inference speed of the controller is about 41.3 MFLIPS (fuzzy logic inference per second) and power consumption is 3.2 mW. Show more

Keywords: A/D converter, CMOS fuzzy controller, current mode circuits, defuzzifier, fuzzifier, fuzzy logic

DOI: 10.3233/JIFS-191672

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Arimany-Serrat, Núria | Farreras-Noguer, Àngels

Article Type: Research Article

Abstract: This article presents an economic and financial analysis of the big wine companies in four of the sector’s leading territories: Catalonia, La Rioja, Languedoc-Roussillon and Emilia Romagna. The different sectors are compared over a seven-year period from 2008–2016. Financial indicators are used which are supported by the literature and built using information from the SABI and AMADEUS databases. The article first characterizes the areas under study and provides a review of the literature before going on to present the empirical study with the appropriate constrasts to explain the economic and financial health of these companies representative of the sector and …especially their profitability. Show more

Keywords: Wine sector, Catalonia, La Rioja, Llenguadoc-Roussillon, Emilia-Romagna, Economic financial analysis, profitability

DOI: 10.3233/JIFS-179646

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Fezai, Radhia | Mansouri, Majdi | Abodayeh, Kamal | Nounou, Hazem | Nounou, Mohamed | Messaoud, Hassani

Article Type: Research Article

Abstract:  In this paper, a novel fault detection and isolation (FDI) framework based on kernel PCA (KPCA) and generalized likelihood ratio test (GLRT) that is capable of detecting and identifying faults is developed. Specifically, three main objectives are addressed. First, system model identification and residuals generation are addressed using KPCA model. Second, KPCA-based GLRT method is proposed to detect different types of faults in the systems. Third, partial KPCA (PKPCA)-based GLRT is developed for fault isolation. The proposed approach aims to apply a structured PKPCA -based GLRT to a set of sub-models. The fault detection and isolation performances using PKPCA-based GLRT …are illustrated through two examples: a simulated continuous stirred tank reactor (CSTR) data and an air quality monitoring network data. The obtained results demonstrate the effectiveness of the partial KPCA-based GLRT method over the partial PCA-based GLRT method. Show more

Keywords: Partial kernel principal component analysis (PKPCA), fault detection and isolation (FDI), generalized likelihood ratio test (GLRT), continuous stirred tank reactor (CSTR), air quality monitoring networks (AQMN)

DOI: 10.3233/JIFS-191525

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Reyes-Zambrano, Gary | Lanzarini, Laura | Hasperué, Waldo | Bariviera, Aurelio F.

Article Type: Research Article

Abstract:  Technological progress facilitates recording and collecting information on vehicles’ GPS trajectories on public roads. The intelligent analysis of this data leads to the identification of extremely useful patterns when making decisions in situations related to urbanism, traffic and road congestion, among others. This article presents a GPS trajectory clustering method that uses angular information to segment the trajectories and a similarity function guided by a pivot. In order to initialize the process, it is proposed to segment the region to be analyzed in a uniform way forming a grid. The obtained results after applying the proposed method on a real …trajectories database are satisfactory and show significant improvement in comparison with the methods published in the bibliography. Show more

Keywords: Segmentation, clustering, GPS trajectories, intelligent transportation systems

DOI: 10.3233/JIFS-179644

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2020

Authors: Pesantez-Narvaez, Jessica | Guillen, Montserrat

Article Type: Research Article

Abstract: Logistic regression as a modelling technique of rare binary dependent variables with much fewer events (ones) than non-events (zeros) tends to underestimate their probability of occurrence. The vast literature devoted to the prediction of rare binary data identifies several ways to improve predictive performance by making modifications to the likelihood estimation. We propose two weighting mechanisms for incorporation in a pseudo-likelihood estimation that improve the predictive capacity of rare binary responses in data collected in complex surveys. We multiply sampling weights by specific correctors that lead to lower root mean square errors for event observations in almost all deciles. A …case study is discussed where this method is implemented to predict the probability of suffering a workplace accident in a logistic regression model that is estimated with data from a survey conducted in Ecuador. Show more

Keywords: Survey data, sampling design, uncommon events, weighting, pseudo-likelihood

DOI: 10.3233/JIFS-179641

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Qiao, Sha | Zhu, Ping

Article Type: Research Article

Abstract:  A large number of studies have investigated the systems of fuzzy relation equations and inequalities, which have a much wider field of application. In this paper, we study several types of systems of fuzzy relation equations and inequalities consisting of a given family of k -ary fuzzy relations, where natural number k  ≥ 2, and three unknown fuzzy relations over complete residuated lattices and meet-continuous lattices. Their solutions are triples of fuzzy relations. For the systems of fuzzy relation inequalities, we give the greatest solutions contained in a given triple of fuzzy relations, the least solutions containing a given triple of …fuzzy relations, or give maximal solutions contained in or containing a given triple of fuzzy relations, or belonging to a given interval of triples of fuzzy relations over complete residuated lattices and complete meet-continuous lattices. For the systems of fuzzy relation equations, we present a method of computing maximal solutions contained in a given triple of fuzzy relations and a method of computing minimal solutions containing a given triple of fuzzy relations. Furthermore, we provide some conditions under which there exist the greatest solutions contained in and the least solutions containing a given triple of fuzzy relations. Show more

Keywords: Fuzzy relation, fuzzy relation equation, fuzzy relation inequality, complete residuated lattice, complete meet-continuous lattice

DOI: 10.3233/JIFS-191695

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-22, 2020

Authors: Olalekan, Adaraniwon Amos | Bin, Mohd Omar

Article Type: Research Article

Abstract:  In this paper, a deterministic inventory model for deteriorating items with linear deterioration rate is proposed. Demand follows a power pattern. Shortages are permitted and partially backlogged. An optimal solution is derived to minimizes the total average cost. Numerical examples are given, and sensitivity analysis carried out to show how the optimal decisions are affected by changes in different parameters in the model. Graphical representation of the convexity of the total cost against the decision variables shows the efficiency and reliability of the model.

Keywords: Inventory, power demand pattern, deterioration, linearly, shortages

DOI: 10.3233/JIFS-191323

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Lee, Woo-Joo | Jhang, Hyo-Jin | Hoe Choi, Seung

Article Type: Research Article

Abstract:  Soccer recently has become an intellectual game by predicting the outcome of games. In this study, we use path analysis to find the variable that affects the outcome of the Korea National Football Team (KNFT) matches the most, and consequently the odds of victory, defeat, or a draw, as announced by the betting company. We will also investigate the influence of the variables inferred from the path analysis and Korea’s ELO Rating on the difference between scoring and losing points of the KNFT. We will represent the dividend and the difference between scoring and losing points as fuzzy numbers using …the fuzzy decomposition, and then infer the fuzzy regression model for the result of the KNFT’s match. For this purpose, we use data on 113 games of the KNFT from September 2011 to June 2019 and the dividend rate of the KNFT obtained from Wise Toto company. Show more

Keywords: ELO rating, dividend, path analysis, fuzzy partition, regression analysis

DOI: 10.3233/JIFS-191288

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Salazar-Elena, Juan Carlos | López, Asunción | Guimón de Ros, José | Cancino, Christian A.

Article Type: Research Article

Abstract: Since the pioneering work of David J. Teece (“Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy”, Research Policy 15, 1986), the concept of “appropriability regime” – defined as the level of threat stemming from potential imitators in the firm’s environment– has been useful in describing specific sectoral patterns at the aggregate level. However, there have been few attempts to formally prove the impact of different regimes on knowledge management strategies at the firm-level. Using firm-level longitudinal data from software and hardware sectors in Spain, we show that differences in appropriability regimes condition the profitability of open …innovation strategies, and also induce specific patterns in firms’ knowledge management strategies. More specifically, we show that the appearance of diminishing returns from an open innovation strategy is more accelerated in firms immersed in weaker regimes (i.e. firms facing more threats from potential imitators). We also show that this is due to the fact that such firms must resort to more complex (and costly) practices that go far beyond the legal protection of intellectual property, internalizing other management practices related to productive capacity and the commercialization of innovations. Show more

Keywords: Innovation, knowledge management, appropriability regime, imitation threat

DOI: 10.3233/JIFS-179643

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Wu, Huaiguang | Xie, Pengjie | Zhang, Huiyi | Li, Daiyi | Cheng, Ming

Article Type: Research Article

Abstract: The chest X-ray examination is one of the most important methods for screening and diagnosing of many lung diseases. Diagnosis of pneumonia by chest X-ray is one of the common methods used by medical experts. However, the image quality of chest X-Ray has some defects, such as low contrast, overlapping organs and blurred boundary, which seriously affects detecting pneumonia in chest X-rays. Therefore, it has important medical value and application significance to construct a stable and accurate automatic detection model of pneumonia through a large number of chest X-ray images. In this paper, we propose a novel hybrid system for …detecting pneumonia from chest X-Ray image: ACNN-RF, which is an adaptive median filter Convolutional Neural Network (CNN) recognition model based on Random forest (RF). Firstly, the improved adaptive median filtering is employed to remove noise in the chest X-ray image, which makes the image more easily recognized. Secondly, we establish the CNN architecture based on Dropout to extract deep activation features from each chest X-ray image. Finally, we employ the RF classifier based on GridSearchCV class as a classifier for deep activation features in CNN model. It not only avoids the phenomenon of over-fitting in data training, but also improves the accuracy of image classification. During our experiment, the public chest X-ray image dataset used in the experiment contains 5863 images, which comprises 4265 frontal-view X-ray images of 1574 unique patients. The average recognition rate of pneumonia is up to 97% by the proposed ACNN-RF. The experimental results show that the ACNN-RF identification system is more effective than the previous traditional image identification system. Show more

Keywords: Chest X-ray, CNN, adaptive median filter, RF, image classification

DOI: 10.3233/JIFS-191438

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Dong, Hongwei | Yang, Liming

Article Type: Research Article

Abstract:  Symmetric loss functions are widely used in regression algorithms to focus on estimating the means. Huber loss, a symmetric smooth loss function, has been proved that it can be optimized with high efficiency and certain robustness. However, mean estimators may be poor when the noise distribution is asymmetric (even outliers caused heavy-tailed distribution noise) and estimators beyond the means are necessary. Under the circumstances, quantile regression is a natural choice which estimates quantiles instead of means through asymmetric loss functions. In this paper, an asymmetric Huber loss function is proposed to implement different penalty for overestimation and underestimation so as …to deal with more general noise. Moreover, a smooth truncated version of the proposed loss is introduced to enhance stronger robustness to outliers. Concave-convex procedure is developed in the primal space with the proof of convergence to handle the non-convexity of the involved truncated objective. Experiments are carried out on both artificial and benchmark datasets and robustness of the proposed methods are verified. Show more

Keywords: Support vector regression, training in the primal, robustness, asymmetric Huber loss, concave-convex procedure

DOI: 10.3233/JIFS-191429

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Liao, Shangchun | Li, Gongfa | Li, Jiahan | Jiang, Du | Jiang, Guozhang | Sun, Ying | Tao, Bo | Zhao, Haoyi | Chen, Disi

Article Type: Research Article

Abstract: SEMG signal is a bioelectrical signal produced by the contraction of human surface muscles. Human-computer interaction based on SEMG signal is of great significance in the field of rehabilitation robots. In this study, a feature extraction method of SEMG signal based on activated muscle regionis proposed, which is based on the study of activated muscle regionin human forearm and hand movement. At the same time, the main research object of this study is the multi-object intergroup SEMG signal which is closer to the practical application environment. The new feature extracted is fused with the sample entropy feature and the wavelength …feature to obtain better signal features. After combining the fusion feature with KNN algorithm, the hand motion pattern recognition and classification between multi-object groups is carried out. The combination of the fusion feature and KNN classification algorithm can achieve 91.05% in the multi-object intergroup hand motion classification. This method has lower computational cost without expensive hardware support, and improves the robustness of hand motion recognition based on EMG signals. Show more

Keywords: Gesture recognition, EMG signal, activated muscle region, feature extraction

DOI: 10.3233/JIFS-179558

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Madadi, Masoumeh | Saadati, Reza

Article Type: Research Article

Abstract:  We attempt to solve some bi-additive θ -random operator inequalities and use the fixed point technique to prove the fuzzy version of Hyers-Ulam-Rassias stability of them.

Keywords: Hyers-Ulam-Rassias stability, bi-additive θ-random operator inequality, fuzzy sets, 54H20, 46L05, 39B62, 43A22

DOI: 10.3233/JIFS-191482

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Taimoor, Muhammad | Aijun, Li

Article Type: Research Article

Abstract: An online fault detection, isolation, and reconstruction strategy is proposed for actuators and sensors fault detection of an aircraft. For increasing the fault detection capabilities, the Extended Kalman Filter (EKF) is used for the weight updating parameters of multi-layer perceptron (MLP) neural network. The main purpose of using the EKF is to make the weight updating parameters of MLP adaptive in order to increase the fault detection, isolation and reconstruction preciseness, efficiency and rapidness compared to the conventional MLP where the fixed learning rate due to which it has slow response to faults occurrence. Because of the online adaptation of …weighting parameters of MLP, the preciseness of the faults detection is increased. For testing and validation of the proposed strategy, the nonlinear dynamics of Boeing 747 100/200 are used. Results demonstrate that the proposed strategy has better accuracy and rapid response to fault detection compared to convention multi-layer perceptron neural network based faults detection schemes. Show more

Keywords: Actuators, sensors, fault detection and isolation, aircraft, neural networks, nonlinear systems

DOI: 10.3233/JIFS-191627

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2020

Authors: Barberà-Mariné, M. Glòria | Fabregat-Aibar, Laura | Sorrosal-Forradellas, M. Teresa | Terceño, Antonio

Article Type: Research Article

Abstract: The main purpose of this article is to analyze the survival capacity of mutual funds based on their characteristics. The methodology used to meet this objective is Self-Organizing Maps (SOM), a type of Artificial Neural Network that allows patterns to be grouped together according to their similarity, enabling us to classify mutual funds into surviving funds and disappeared funds. We consider the following variables: age, size, investment flows, performance, volatility, and Morningstar rating. We use a sample of 1,617 Spanish mutual funds, of which 943 had disappeared between 2004 and 2016. The results obtained indicate that SOM accurately classifies 80% …of mutual funds. Therefore, SOMs are effective instruments for classifying the disappearance of Spanish mutual funds and the variables used to define them can explain their survival capacity. Show more

Keywords: Mutual funds, self-organizing maps, spanish market, survival capacity, surviving funds, disappeared funds

DOI: 10.3233/JIFS-179640

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Dammak, Fatma | Baccour, Leila | Alimi, Adel M.

Article Type: Research Article

Abstract:  In this work we propose an approach of multi-criteria decision making (MCDM) using TOPSIS and VIKOR methods under interval-valued intuitionistic fuzzy (IVIF) sets and possibility theory. We are interested to study positive and negative ideal solutions to propose new formulas. Indeed, these solutions are presented with many formulas in literature [1, 2 ] which could cause ambiguity [3 ]. Due to the importance of possibility theory in resolution of many problems, we propose to use possibility measure for positive ideal solution and necessity measure for negative ideal solution under interval valued intuitionistic fuzzy sets. According to this, TOPSIS and VIKOR …are modified to obtain new approaches. The latter are applied to an example from literature using IVIF data. This example permits to assess the investment projects problem for ranking different projects. The found results showed different solutions from that existing in literature which can give more choice to decision makers with additional information due to use of possibility measures. Show more

Keywords: Interval-valued intuitionistic fuzzy sets, possibility measure, multi-criteria decision making, necessity measure, TOPSIS, VIKOR

DOI: 10.3233/JIFS-191223

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Jing, Xin | Li, Shihao | Cheng, Jing | Guo, Junjun

Article Type: Research Article

Abstract: In order to solve the problem of resource waste in colleges and universities, this paper proposes a multidimensional situational information fusion method, which can be used to normalize, analyze and predict the multi-source data such as natural, humanistic and spatio-temporal data on campus so as to meet the application requirements for high-level decision-making. With this method, firstly, the event object model is used to normalize multi-source data. Then, the multidimensional situational information fusion mechanism of twice reasoning is used to obtain the real-time situation and equipment control scheme of the campus so that real-time intelligent semantic understanding is realized. In …the process of reasoning, the improved KNN prediction model is used to predict situational trends, and the prediction information is used to continue deep reasoning and mining. Finally, the real-time energy-saving regulation is carried out through control instructions. In addition, through simulation verification, experimental results show that this method can quickly identify, integrate, and predict the current real-time situation and generate reasoning results, and finally achieve the goal of intelligent control for energy saving on campus. Show more

Keywords: Smart campus, energy saving, situational information fusion, intelligent control

DOI: 10.3233/JIFS-191513

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Shazad, Aqeel | Rasham, Tahair | Marino, Giuseppe | Shoaib, Abdullah

Article Type: Research Article

Abstract:  The purpose of this article is to establish fixed point results for a pair of α ∗ -dominated fuzzy mappings fulfilling generalized locally new α ∗ - ψ -Ćirić type rational contractive conditions on a closed ball in complete dislocated metric spaces. Example and application are given to demonstrate the novelty of our results. Our results extend several comparable results in the existing literature.

Keywords: Fixed point, complete dislocated metricspace, α∗-dominated mapping, α∗- ψ-Ćirić type rational contraction, graphic contraction, fuzzy mappings, 46S40, 47H10, 54H25

DOI: 10.3233/JIFS-191020

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Yang, Kai | Wang, Rui | Yang, Lixing

Article Type: Research Article

Abstract:  Failures on hub-and-spoke (H&S) network components (i.e., node and arc) of a road-rail intermodal transport (RRIT) system can give rise to severe degradation of the entire system reliability. This paper aims at developing a fuzzy reliability optimization approach for the RRIT system, which can be interpreted as a parallel-series system. To begin with, we provide a definition for the RRIT system reliability and relevant functions and subsequently, a fuzzy possibility measure-based optimization model. Different from previous studies, this model focuses on maximizing the network performance in terms of reliability by locating intermodal hubs for delivering flows among origin-destination (O-D) nodes. …Next, we further discuss the complexity of the proposed model which has proven to be NP-hard. Hence, we use the tabu search (TS) algorithm with a two-dimensional array-based representation and two types of move operators to solve the proposed model and obtain optimal/near-optimal solutions for realistic instance sizes. Finally, we conduct a case study based on the well-known Turkish network to demonstrate the superiority of proposed model and the effectiveness of developed methods. Show more

Keywords: Road-rail intermodal transport, hub-and-spoke network, parallel-series system, fuzzy reliability, TS algorithm

DOI: 10.3233/JIFS-191010

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Ko, Jung Mi | Kim, Yong Chan

Article Type: Research Article

Abstract:  We introduce the concepts of fuzzy join complete lattices and Alexandrov L -pretopologies in complete residuated lattices. We show that fuzzy join complete lattices, Alexandrov L -pretopologies, fuzzy meet complete lattices and Alexandrov L -precotopologies are equivalent. Moreover, we define L -preinterior operators (resp. L -preclosure operators) as a viewpoint of fuzzy joins (resp. fuzzy meet) and fuzzy rough sets. Furthermore their properties and examples are investigated.

Keywords: Complete residuated lattices, fuzzy join(meet)-complete lattices Alexandrov L-pre(co)topologies, fuzzy rough sets

DOI: 10.3233/JIFS-191344

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Amirbagheri, Keivan | Merigó, José M. | Guitart-Tarrés, Laura | Nuñez-Carballosa, Ana

Article Type: Research Article

Abstract:  This study proposes, through weighted averages and ordered weighted averaging operators, a new aggregation system for the investigation of average gases emissions. We present the ordered weighted averaging operators gases emissions, the induced ordered weighted averaging operators gases emissions, the weighted ordered weighted averaging operators gases emissions and the induced probabilistic weighted ordered weighted averaging operators gases emissions. These operators represent a new way of analyzing the average gases emissions of different variables like countries or regions. The work presents further generalizations by using generalized and quasi-arithmetic means. The article also presents an illustrative example with respect to the calculations …of the average gases emissions in the European region. Show more

Keywords: Green-house gases emission, aggregation operators, decision making, ordered weighted average

DOI: 10.3233/JIFS-179635

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Dehghan, Motahareh | Sadeghiyan, Babak | Khosravian, Erfan

Article Type: Research Article

Abstract:  In this paper, we present a protocol for secure resolution of collision between aircraft, while their corresponding trajectories are kept private. For privacy reasons, we assume that each aircraft’s position, heading and velocity are not available to all aircraft involved in the protocol. Our new secure protocol is based on an algorithm, which is for collision resolution of aircraft, without considering the privacy requirement. Our approach is Secure Multi-party Computation. To present our Secure Multi-party Collision Resolution Protocol, we propose a new Secure Sorting Protocol and a Modified Distributed Oblivious Transfer Protocol. We also take advantage of employing a …Secure Multi-party Collision Detection Protocol, a Homomorphic Encryption, a Secure Comparison Protocol, and a Secure Maximum Finding Protocol. To prove the security of our proposed protocol and its sub-protocols, we use the Ideal/ Real Simulation Paradigm. The communication complexity of our proposed protocol is in O  (n 2 ), and its computation complexity is in O(n) . We have also done a simulation for the execution of our proposed protocol for multiple moving aircraft, to show its practicality. Show more

Keywords: Privacy, collision detection and resolution, line segment intersection algorithm, exact and inexact collision

DOI: 10.3233/JIFS-190675

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2020

Authors: Yang, Hong | Gong, Zengtai

Article Type: Research Article

Abstract:  In this paper, we proposed an iterative procedure based on Landweber iterative methods to solve fuzzy Fredholm integral equations of the first kind. In addition, this research be based on a strictly convex fuzzy number space and the Riemann integral of fuzzy-number-valued function which is taken value in the space. The error estimation of the proposed method in terms of uniform and partial modulus of continuity was given. The generalized difference of fuzzy numbers was controlled and estimated reasonably. And it was avoided to compute the generalized difference of fuzzy numbers during the iterations. Finally, an illustrative example is included …in order to demonstrate the accuracy and the convergence of the proposed method. Show more

Keywords: Fuzzy numbers, Fuzzy Integral equation, Iterative method, Uniform modulus of continuity, Partial modulus of continuity

DOI: 10.3233/JIFS-190972

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2020

Authors: Zurita, Gustavo | Merigó, José M. | Lobos-Ossadón, Valeria | Mulet-Forteza, Carles

Article Type: Research Article

Abstract:  Computer Science degrees are very popular currently among institutions worldwide. The proliferation of these programs in different universities has led to the creation of rankings for classifying programs according to their prestige and quality. However, these rankings do not specify the quality of research. This study develops a bibliometric overview of all the journals that are currently indexed in the Web of Science (WoS) database in any of the seven categories connected to Computer Science research. These categories include Artificial Intelligence, Cybernetics, Hardware and Architecture, Information Systems, Interdisciplinary Applications, Software Engineering and Theory and Methods. This study aims to identify …the leading institutions over the last 25 years (1991–2015) in each area selected according to a wide range of bibliometric indicators. The results indicate that American universities are the most influential in Computer Science research. This study concludes that Computer Science traverses many institutions. Show more

Keywords: Computer science, bibliometrics, institutions, web of science, citations, ranking

DOI: 10.3233/JIFS-179636

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Cancino, Christian A. | Guimón, José | Salazar-Elena, Juan C. | La Paz, Ariel I.

Article Type: Research Article

Abstract:  In the last few decades, the number of academic articles focused on digital business has grown exponentially. The aim of this study is to present the evolution of academic research in digital business between 1990 and 2015. The analysis concentrates on identifying the most productive and influential journals in this field of research, as well as the leading authors. The results show a strong increase in digital business research during that period due to the development of an important number of specialized information systems journals, but also with publications in several disciplines of the management field. The latter reflects the …multidisciplinary nature of this field of research, including not only studies with a focus on management information systems, but also on strategy, marketing, operations and more. Show more

Keywords: Digital Business, information systems and technologies, bibliometrics, web of science

DOI: 10.3233/JIFS-179638

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Vicedo, Pau | Gil, Hermenegildo | Oltra-Badenes, Raúl

Article Type: Research Article

Abstract:  This work conducts bibliometric research into publications during the period 1999 to early 2018. The aim of this study is to help gain a better understanding of the publications covering CSF and ERP implementations all over the world. The study includes the most cited articles, most cited authors and most influential institutions as well as the most prolific countries. A database of 301 articles from 86 different institutions and 48 countries has been documented and analyzed. The results indicate that this field is growing significantly over time and a small number of US institutions are currently the most productive in …this field. Show more

Keywords: CSF, ERP, bibliometrics, Web of Science

DOI: 10.3233/JIFS-179639

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Otero-González, L. | Ibragimova, D. | Cunil, O. Martorell | Rodríguez Gil, L.I.

Article Type: Research Article

Abstract:  The study analyses the effectiveness of the Early Warning System (EWS) for forecasting bank defaults during the recent financial crisis based on Moody’s KMV Expected Default Frequency (EDF) measure and accounting ratios using a sample of European listed banks. The Bank Financial Strength ratings D + and below are used as a bank default indicator. Independent variables include 1-year and 5-year EDFs, one for the adverse selection effect and another for accounting ratios. Our results show that EDF metrics combined with four CAMEL covariates and the variable capturing adverse selection are able to predict the defaults of European banks up …to 8 quarters before an event. When comparing the model with another only including the EDF indicator, the statistical significance improves considerably, suggesting that added variables provide additional information and power to the model. This study proposes possible improvements to the EWS which could be useful to identify inputs to incorporate in intelligent models. Show more

Keywords: Early warning systems, CAMEL models, distance to default, expected default frequency, banks

DOI: 10.3233/JIFS-179637

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Fazil, Mohd | Abulaish, Muhammad

Article Type: Research Article

Abstract:  Twitter is a popular microblogging platform, which facilitates users to express views and thoughts on day-to-day events using short texts limited to a maximum of 280 characters. However, it is generally targeted by socialbots for political astroturfing, advertising, spamming, and other illicit activities due to its open and real-time information sharing and dissemination nature. In this paper, we present a socialbots analysis-driven graph-based approach for identifying coordinated campaigns among Twitter users. To this end, we first present statistical insights derived from the analysis of logged data of 98 socialbots, which were injected in Twitter and associated with …top-six Twitter using countries. In the analysis, we study and present the impact of socialbots’ profile features, such as age and gender on infiltration. We also present a multi-attributed graph-based approach to model the profile attributes and interaction behavior of users as a similarity graph for identifying different groups of synchronized users involved in coordinated campaigns. The proposed approach is experimentally evaluated using four different evaluation parameters over a real dataset containing socialbots’ trapped user profiles. The evaluation of identified campaigns in the form of clusters reveals the traces of spammers, botnets, and other malicious users. Show more

Keywords: social network analysis, coordinated campaign, socialbots infiltration, socialbots characterization, twitter spam

DOI: 10.3233/JIFS-182895

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Qin, Haiyong | Attia, Raghda A.M. | Khater, Mostafa M.A. | Lu, Dianchen

Article Type: Research Article

Abstract: This research paper studies the soliton waves of the (N  + 1) dimensional time-fractional conformable Sinh-Gordon equation by the implementation of the modified Khater method. This equation studies surfaces of constant negative curvature, such as the Gauss-Codazzi equation for surfaces of curvature. Using the Painlevé property is employed to support the modified Khater method in formulating of abundant traveling wave solutions. The performance of the used technique emphasizes the power, effect, and ability for applying to many nonlinear evolution equations.

Keywords: (N + 1) dimensional time-fractional sinh-gordon equation, painlevé property, modified auxiliary equation method, nonlinear wave, conformable fractional derivative

DOI: 10.3233/JIFS-179560

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Ben Dhahbi, Anis | Chargui, Yassine | Boulaaras, Salah | Trabelsi, Adel

Article Type: Research Article

Abstract:  In the context of the development of our study (S. Mohammed et al.) entitled “Theoretical calculation of positron-nuclear emulsion image resolution using Geant4 code” published on 2017, this research will evaluate the optimization of the image resolution of the Positron Emission Tomography (PET) when the so-called nuclear emulsion technology is introduced into tumor imaging. Upgraded and more reliable FLUKA Monte-Carlo simulation codes were performed in order to simulate a punctual source of 1 MeV positrons, emitting particles in all directions through a nuclear emulsion medium. Two new methods dedicated for the vertex reconstruction leading to an accurate recognition of the …positron source are presented in this work. Moreover, this research focuses on the effects of the technical obstructions that would affect the PET imaging procedures using the nuclear emulsion, such as the scanning microscope efficiency and the actual accuracy of the slope and position measurement of the particle track on the emulsion. Taking such parameters into considerations gave a more precise and realistic estimate of the so-optimized image resolution for the PET medical imaging system. Show more

Keywords: Positron emission tomography, nuclear emulsion, PET, ECC, image resolution

DOI: 10.3233/JIFS-179561

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Cai, Jingcao | Lei, Deming

Article Type: Research Article

Abstract:  Distributed scheduling has attracted much attention in multiple factories. However, uncertainties are often neglected in the previous works and this neglecting may result in the low value of the obtained schedule. In this study, fuzzy distributed scheduling is addressed in two-stage hybrid flow shop with sequence-dependent setup times(SDST) which is a frequently studied constraint in single factory and seldom handled in multiple factories. A collaborative variable search (CVS) is proposed to optimize total agreement index and fuzzy makespan simultaneously. Seven neighborhood structures and two global search operators are used in two cooperated variable search parts to generate high quality solutions. …Experiments are conducted and the computational results reveal that CVS has promising advantages on the considered fuzz distributed scheduling problem. Show more

Keywords: collaborative variable search, fuzzy scheduling, distributed scheduling, two-stage hybrid flow shop, sequence-dependent setup times

DOI: 10.3233/JIFS-191175

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: López, Carles | Linares-Mustarós, Salvador | Viñas, Josep

Article Type: Research Article

Abstract: This paper addresses the need for a tool that makes use of expert opinion to determine whether individual public administration services should be outsourced. It begins by analyzing the specific characteristics of the public sector in relation to outsourcing and continues with a description of the main services, both mandatory and otherwise, provided by a local corporation, classifying them according to whether they are aimed at people, the territory or infrastructure. Fuzzy math tools are then used, by means of an endecadarian scale, to allow diverse experts to state the degree to which they agree on the possible outsourcing of …a public service. In order to facilitate their decision-making, experts can offer a confidence interval of that degree. From the different intervals obtained through this process, a decision method is presented that uses the fuzzy logic tool “experton” as a basis. Several examples clarify and exemplify the method. Show more

Keywords: Outsourcing, public sector, fuzzy logic, theory of expertons, experton’s expectation, expected value of the experton’s expectation

DOI: 10.3233/JIFS-179631

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Cabrera-Flores, Mayer R. | Peris-Ortiz, Marta | León-Pozo, Alicia

Article Type: Research Article

Abstract: This paper explores the relationship between knowledge, innovation, and profit-making in the craft beer industry in Baja California, Mexico. The research highlights the cultural nature of this industry, in which the depth of culture and tradition bolster the capacity for innovation. One source of interest in the study of cultural industries is the importance of businesses in regional development, as is happening in the Baja California region with craft beer. At its core, this study draws on the SECI model as a reference to highlight the different ways in which knowledge and learning combine to produce new forms of processes …or products or break into new market segments. This empirical study is based on the fuzzy-set qualitative comparative analysis method (FsQCA), which serves to identify sequences or combinations of knowledge and learning that lead to innovation and profit. Show more

Keywords: Craft beer industry, tacit knowledge, explicit knowledge, formal learning, fuzzy-set qualitative comparative analysis (FsQCA)

DOI: 10.3233/JIFS-179630

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Faixó, Ferran Herraiz | Arroyo-Cañada, Francisco-Javier | López-Jurado, María Pilar | Lauroba Pérez, Ana M.

Article Type: Research Article

Abstract: Currently, cities are facing great challenges such as the population growing, citizen wellbeing, externalities management or environmental deterioration. The search for solutions are making significant inroads into the incorporation of ICT in them and subsequent large-scale digitalization such as programmable economy (PE) applications, offering the possibility to develop new approaches over these issues, in particular which related to sustainability management. Operating under a fuzzy numbers methodology and FIS (Fuzzy Inference System), the present exploratory work shows a new approach to city urban congestion management by deploying PE applications, which include some disruptive inputs such as the Internet of value, blockchain/DLT …(distributed ledger technology), smarts contracts, digital assets and the monetization, all of this combined with the human motivation. Show more

Keywords: Programmable economy, blockchain, smart cities, urban congestion, fuzzy sets

DOI: 10.3233/JIFS-179632

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Nicolas, Carolina | Rojas-Mora, Julio | Valenzuela-Fernández, Leslier

Article Type: Research Article

Abstract: The aim of this study is to examine the incidence of economic activity on soft innovation in the mining sector. Through a global analysis of indirect incidents and using the theory of forgotten effects. Thus, the case of the mining industry in Chile was analyzed, given that it is one of the industries that contributes the most to GDP in Chile. The empirical study was carried out through the application of a structured survey towards three experts from the mining sector. In addition, the study concludes with evidence that oil price has a direct incidence on investments in mining and …economic expectations, and indirectly in average income middle managers, market share of the company in the mining sector, and growth of imports and exports in the mining sector. Show more

Keywords: Soft innovation, mining industry, forgotten effects theory, monte carlo method

DOI: 10.3233/JIFS-179633

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: López-Guauque, Jaime A. | Gil-Lafuente, Anna M.

Article Type: Research Article

Abstract: This paper presents a general overview and a long-term comparison in fuzzy logic research published between 1965 and 2017, obtained via Web of Science. The paper analyzes the growth, impact, trends and regional localization of fuzzy research. Conventional, sophisticated among others bibliometric indicators have applies. It aggregates the information according to different levels and criteria including researchers, publications, institutions, or countries. A global perspective have been provided through comparisons of regional aggregates and compound annual growth rates that strengthen the indicators applied in this article. The results permit to visualize the influence, importance, evolution and performance of the fuzzy research …as well its contribution to, and transversality with other fields. The findings show that China continues to be a leader in number of contributions. There has been a recent relative decline in the United States contributions overall. Asian and African contributions to scientific literature have grown noticeably. The results also provide a framework for the use of indicators adjusted to specific contexts and relevant information for future research. Show more

Keywords: Fuzzy logic, bibliometrics, scientometrics, web of science, research indicators, H-index, CAGR

DOI: 10.3233/JIFS-179634

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Verma, Rajkumar

Article Type: Research Article

Abstract: Linguistic decision-making tools are very useful in determining the solution to real-life decision problems. In order to represent the complex fuzzy qualitative information more accurately, this paper introduces a novel concept called linguistic trapezoidal fuzzy intuitionistic fuzzy set (LTFIFS), where the degrees of membership (MS) and non-membership (NMS) are represented by trapezoidal fuzzy linguistic numbers. Further, work defines some basic operational laws, score and accuracy values, and a comparison method for LTFIFNs with a brief study of related properties. To aggregate different LTFIFNs, we develop several weighted arithmetic and weighted geometric aggregation operators such as the LTFIFWA operator, the LTFIFOWA …operator, the LTFIFOWAWA operator, the LTFIFWG operator, the LTFIFOWG operator, and the LTFIFOWGWG operator. Paper also establishes several important properties and particular cases of these operators. Furthermore, by using proposed aggregation operators, we formulate a decision-making approach for solving group decision-making problems under the LTFIF environment with multiple attributes. Finally, the paper presents a real-life decision problem to validate the effectiveness and flexibility of the newly given approach. Show more

Keywords: Linguistic variable, trapezoidal fuzzy linguistic fuzzy variable, linguistic intuitionistic fuzzy numbers, aggregation operators

DOI: 10.3233/JIFS-181197

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-44, 2020

Authors: Wang, Wei | Hu, Xiaohui | Wang, Mingye

Article Type: Research Article

Abstract: With the development of Internet technology, the growth of network services is accelerating. For more and more network service requests, how to ensure the response speed and query accuracy required by users is a huge challenge. In order to realize fast clustering of large data business request data and improve the accuracy of clustering. This paper presents a data fuzzy clustering algorithm based on Adaptive Incremental learning time series. The algorithm defines large data clustering in time series, and the incremental time series clustering method is used. Firstly, the complexity of network data is reduced by data compression, and then …time series data clustering based on service time similarity is carried out. In this paper, the time series fuzzy clustering algorithm based on Adaptive Incremental Learning inherits the clustering structure information obtained by previous clustering. Initialize the current clustering process, and then search the outlier samples in the current data block adaptively without setting parameters. Automatically create new clusters from outlier samples, and finally check empty cluster recognition. Identification determines whether certain clusters need to be deleted to ensure the efficiency of subsequent cluster processes. The experimental results show that the algorithm has good clustering accuracy and efficiency for isochronous and unequal time series. Show more

Keywords: Network data, adaptive incremental learning, time series, fuzzy clustering algorithm

DOI: 10.3233/JIFS-179624

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Wu, Jian-Zhang | Beliakov, Gleb

Article Type: Research Article

Abstract:  We propose a general notion of lower k -order representative capacity that is totally identified by the smallest k-order coefficients in one or another equivalent representation, and the k -additive, k -maxitive and k -tolerant capacities are just its special cases. We further construct its dual notion, the upper k -order representative capacity, which is accordingly determined by n  - 1 to n  - k -order representation coefficients and takes k -minitive and k -intolerant capacities as its concrete instances. Some particular and important cases of the upper and lower k -order representative capacities based on nonadditivity index as well as simultaneous …interaction indices are introduced and studied. The identification scheme of lower/upper k -order capacity is also given and illustrated. This general framework allows one to tailor and simplify capacities while matching and representing the decision makers preferences in terms of interaction index or other desired representation of capacity. Show more

Keywords: Multicriteria decision making (MCDM), fuzzy measure, lower and upper k-order representative, k-nonadditive, capacity identification

DOI: 10.3233/JIFS-191049

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Yuan, Yana | Chai, Huaqi

Article Type: Research Article

Abstract: The discussion of knowledge management and technological innovation has never stopped, and the discussion of the relationship between the two has not only important practical significance but also profound theoretical significance. The purpose of this paper is to study a new method of knowledge fusion from the perspective of science and technology philosophy. From a new perspective, this paper analyzes defects of subjective tendencies, decision-dependent partial attributes of knowledge source existed in practical applications of management field and proposed a knowledge fusion method based on fuzzy set theory. This paper firstly explains the characteristics of knowledge sources, and transforms knowledge …into a new knowledge layer through combining multi-source knowledge, then improves the connotation, level and self-confidence of knowledge, finally improves the ability of the system to accomplish tasks and goals. Then combine the fuzzy set theory with the knowledge fusion algorithm reasonably and effectively, and obtain the results of knowledge fusion by using evidence synthesis and decision rules, so as to make up for the lack and defects in the knowledge fusion process and solve the uncertainty problem in knowledge reasoning. Finally, through the practical example, merged the fuzzy set theory proposed in this paper into knowledge fusion to deal it, obtain a kind of processing of fuzzy set theory, forming a knowledge fusion method based on fuzzy set theory. Based on fuzzy set theory, obtain the observation results of knowledge fusion algorithm combined with the various warning models, then to discuss and analyze the enterprise warning problem deeply. Therefore, the examples and simulation results show that the advantages in practicality and versatility of knowledge fusion method proposed through fuzzy set theory is higher than the common knowledge fusion method. The method used in the production of manufacturing products can help manufacturing companies improve development quality of product and shorten development cycle of product. Moreover, in the product design industry, it has verified that knowledge fusion can promote the dissemination of knowledge in the field of knowledge management, which helps to share and reuse design knowledge, reduce difficulty of development and improve efficiency of development. Show more

Keywords: Knowledge management, information fusion, fuzzy set theory, fuzzy petri net, knowledge update

DOI: 10.3233/JIFS-179622

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Zhou, Mu | Li, Xinyue | Wang, Yong | Yang, Xiaolong | Tian, Zengshan

Article Type: Research Article

Abstract: In this paper, we derive out an analytical result towards fuzzy error bound of indoor Neighbor Matching based Positioning Algorithm (NMPA). First of all, in a typical Line-of-sight (LOS) environment, we utilize the fuzzy comprehensive evaluation approach to obtain the fuzzy membership of the target in fingerprint matching. Second, we present an analysis of the theoretical relationship between the positioning error of NMPA and different environmental parameters. Third, we work out the fuzzy closed form solution to the positioning error of NMPA concerning the size of environment, the spacing of Reference Points (RPs), number of neighbors, and positions of Access …Points (APs). Finally, relevant experiments verify that the fuzzy error bound proposed in this paper can reflect the influence of different factors of the environment on the performance of the positioning system, thereby, the positioning accuracy can be improved and the deployment costs can be reduced by optimizing the environmental parameters. Show more

Keywords: Indoor localization, fuzzy membership, environmental parameters, error bound, neighbor matching

DOI: 10.3233/JIFS-179590

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Li, Meiqian | Huang, Xianjiu | Zhang, Cailiang

Article Type: Research Article

Abstract:  Intuitionistic fuzzy number, which is an extension of fuzzy number, has been applied in many fields as it considers membership degree and non-membership degree. However, in some circumstances, intuitionistic fuzzy number does not express uncertainty and vagueness well. In order to deal with this problem, a new concept of trapezoidal type-2 intuitionistic fuzzy number(TrT2IFN) is proposed in this paper. Meanwhile, the arithmetical operations of TrT2IFNs are defined. Then, a novel distance measures are proposed by taking advantage of the Hausdorff distance. Additionally, the multi-attributes decision making problem of the TrT2IFN is solved by the grey relational bidirectional projection method. Finally, …the applicability and availability of the proposed method are demonstrated by a numerical example, and the final ranking outcome of alternatives is obtained. This paper provides an effective solution for solving multi-attribute decision making in TrT2IFN environment. Show more

Keywords: Trapezoidal type-2 intuitionistic fuzzy numbers, Arithmetic operations, Score function, Hausdorff distance, Grey relational bidirectional projection method

DOI: 10.3233/JIFS-191174

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Shatanawi, Wasfi | Gupta, Vishal | Kanwar, Ashima

Article Type: Research Article

Abstract:  In this paper, we introduce the notions of E.A and common E.A on modified intuitionistic generalized fuzzy metric space. We utilize our new notions to introduce and formulate some common fixed point theorems on modified intuitionistic generalized fuzzy metric space for coupled maps.

Keywords: Coupled maps, complete subspace, property (E.A), fuzzy metric space (FM-space), common E.A property, modified intuitionistic generalized fuzzy metric space (MIGFM-space)

DOI: 10.3233/JIFS-190541

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Wang, Renqiang | Miao, Keyin | Sun, Jianming

Article Type: Research Article

Abstract: In view of the objectively ambiguous feature of infrared image of unmanned autonomous ship, this paper presents a quantitative method to deal with the ambiguity problem in infrared image by using the fuzzy mathematical model to realize the purpose of intelligent recognition of infrared imaging target. In order to simplify the computation of target recognition and improve the response time and accuracy in the selection of target features in infrared images, three features of target location, radiation distribution and shape are selected for analysis in this paper. The membership functions of these three features are weighted to calculate the confidence, …and the classification and recognition are realized according to the confidence. Finally, the simulation results show that the recognition method proposed in this paper can effectively identify the target, and the recognition rate is very high. Compared with the recognition methods based on neural network and SVM, the recognition distance of this method is longer than that of the latter two methods. Show more

Keywords: Fuzzy mathematical model, unmanned autonomous ship, infrared imaging, intelligent target recognition

DOI: 10.3233/JIFS-179623

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Hashemi, Seyyed Ahmad | Farrokhi, Hamid

Article Type: Research Article

Abstract: Self-Organization networking (SON) consists of function sets which are responsible for automatically reliable configuring, planning and optimizing next generation mobile networks. Effective self-organization functions improve the level of network key performance indicators by determining optimal network setting and continuously finding efficient solutions that will be very hard for experts to distinguish. Most current self-organization networking functions apply rule-based recommended systems to control network resources in which performance metrics are evaluated and the effective actions are performed in accordance with a set of command sequences which such algorithms are too complicated to design, because rules and command sequences should be derived …for each target index during each possible scenario. This research has proposed cognitive wireless networks as a fully intelligent approach to self-organization networking. We generalize the concept of network automation considering fuzzy-based self-organization networking functions as Q-learning problems in which, a framework is described to find the fuzzy optimal solution of linear programming optimization problem. The achieved results prove that the proposed cognitive approach, provides a prominent cellular framework for developing self-organization solutions, particularly where the relevance of metrics to the control indices is not clearly known. Also, assessment of the scheme in multiple-speed scenarios revealed that Q-learning load balancing obtains more accurate results compared to rule-based adaptive load balancing methods. This is particularly correct in dynamic networks, with high-speed users. Show more

Keywords: Next-generation mobile networks, reinforcement learning, handover optimization, load balancing, network automation

DOI: 10.3233/JIFS-191558

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2020

Authors: Nong, Zhonghai

Article Type: Research Article

Abstract: Image recognitionan is an important part of pattern recognition, It has been widely used in modern production and life. Using computer technology and modern information processing technology to complete human visual cognition and understanding. Thus, It have become a hot topic about how to study image recognition based on medical color feature extraction. This study firstly studied the existing literature, explored and analyzed relevant theories and technologies, and studied several algorithms related to current image recognition. Then the image recognition algorithm based on wavelet moment and support vector machine is combined with the artificial intelligence technology based on image feature …extraction theory to establish the color medical image recognition algorithm based on wavelet moment and support vector machine. In order to verify the feasibility and advancedness of the new algorithm, practical experiments are carried out, and the experimental results are compared and analyzed by statistical method. The concrete chart proves the correctness of the conclusion. The final of the new algorithm is proved to be successful. Show more

Keywords: Feature extraction, image recognition, color characteristics, medical image database

DOI: 10.3233/JIFS-179612

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Guo, Rui | Shen, Xuanjing | Kang, Hui

Article Type: Research Article

Abstract: Image segmentation is very important for various fields. With the development of computer technology, computer technology has become more and more effective for image segmentation, and it is studied on the basis of partial differential equations. The curve representation method in plane differential geometry is expounded, with the SegNet-v2 segmentation model analyzed and tested in medical image segmentation. The test results show that the partial differential equation image segmentation algorithm can achieve more accurate segmentation, especially in medical image segmentation, which can achieve good results, and it is worth in practice to further promote.

Keywords: Partial differential equation, image segmentation, algorithm analysis

DOI: 10.3233/JIFS-179614

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Liu, Na

Article Type: Research Article

Abstract: Medical image segmentation is an important step of medical image processing, which divides medical image into thousands of regions and extracts the regions of tissues and organs of interest. The accuracy of segmentation is very important for the follow-up processing of medical image and doctors’ judgment of the real situation of diseases. Medical image segmentation is a classic problem in the field of image segmentation. 3D image reconstruction technology is to obtain 3D structure information from 2D images of objects, to provide users with realistic 3D graphics, and to restore the prototype of objects, so that users can observe and …analyze from multiple perspectives, which greatly improves the accuracy of measurement and the scientific accuracy of medical diagnosis, and plays a very important role in assisting doctors in clinical diagnosis. Based on the three-dimensional image model of MRI, the load variation of the internal oblique muscle can be applied to the finite element analysis of the near end of the patellar tendon. Show more

Keywords: Three-dimensional reconstruction technology, medical image, MRI

DOI: 10.3233/JIFS-179611

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Fan, Ching-Lung

Article Type: Research Article

Abstract: Construction inspection is a crucial mechanism for evaluating the construction quality of public construction in Taiwan. Inspection scores are results based on the experiences or subjective evaluations of auditors. Although general rating principles and procedures are specified, objective standards are not adopted to determine scores and cannot concretely demonstrate actual construction quality. This study integrated the analytic network process (ANP) and fuzzy set (FS) to develop a construction quality index (CQI) model as a concrete indicator and objective standard for evaluating construction quality. Based on past defect data inspected by auditors, dependent factors for defects were established, and the ANP …was employed to calculate the weights of all factors. Subsequently, the frequencies of defects for all items in a construction inspection were multiplied by the factor weights and summed to obtain a set of CQI values. Furthermore, the use of FS reasoning affects important defects (10 items) in project quality and important values (IV). The CQI values obtained were as follows. Grade A was lower than 1.0, Grade B was between 1.0 and 3.0, Grade C was between 3.0 and 5.0, and Grade D was greater than 5.0 (IV). The CQI model is based on the frequency of defects and weights, improves the problem of intuitive on-site ratings provided by auditors, and establishes an objective and simple method for rating construction quality to effectively enhance rating standards for construction inspections. Show more

Keywords: Analytic network process, fuzzy set, construction quality index, construction inspection, grade

DOI: 10.3233/JIFS-190608

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2020

Authors: Najib, Fatma M. | Ismail, Rasha M. | Badr, Nagwa L. | Gharib, Tarek. F.

Article Type: Research Article

Abstract: Recent applications such as sensor networks generate continuous and dynamic data streams. Data streams are often gathered from multiple data sources with some incompleteness. Clustering such data is constrained by incompleteness of data, data distribution, and continuous nature of data streams. Ignoring missing values in incomplete data clustering, especially in high missing rates decreases the clustering performance. Traditional clustering is applied on the whole data without dealing with data distribution. This paper presents an efficient framework called Fuzzy c-means clustering for Incomplete Data streams (FID) that works adaptively with incomplete data streams even with high missing rates. The proposed FID …estimates missing values based on the corresponding nearest-neighbors’ intervals. To overcome the previously mentioned data streams clustering problems, the continuous clustering mechanism is adopted and extended to accurately handle the incomplete data streams. Experimental results using two different data sets prove the efficiency of the proposed FID comparing to the alternative approaches. Show more

Keywords: Data streams, incomplete data clustering, fuzzy clustering, nearest neighbor rule

DOI: 10.3233/JIFS-191184

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Alfaro-García, Victor G. | Merigó, José M. | Alfaro Calderón, Gerardo G. | Plata-Pérez, Leobardo | Gil-Lafuente, Anna M. | Herrera-Viedma, Enrique

Article Type: Research Article

Abstract: This paper presents the results of a citation analysis focusing on the universities and countries represented by publications in 22 highly oriented fuzzy research journals using bibliometric techniques. Bibliometric studies have recently gained significant relevance, and this fact is mainly due to the flexibility and dynamism that new information technologies provide. In our case, the structured gathered materials are thoroughly refined and offer a wide view of the influence that the selected journals have on territories and institutions around the globe. The results show the clear influence of countries located in the Asian continent and the high impact of institutions …in Spain, the United States of America and China. This study sheds light on the visualization of the citation scope of these highly oriented fuzzy research journals with the aim of finding possible common ground for synergy and collaboration. Show more

Keywords: Bibliometrics, fuzzy research, citation analyses, universities, countries

DOI: 10.3233/JIFS-179629

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Salvá, Antonio Socias | Nicolas, Carolina | Rosselló, Patricia Horrach | Mulet-Forteza, Carles

Article Type: Research Article

Abstract: This research aims to explore the impact of the principal worth-creating initiatives in hybrid business management models. The methodology applied is the theory of the forgotten effects, which assesses some direct and indirect relationships to determine causes and effects in the value-creation in non-profit organizations. The main contribution of this study shows that the non-foreseen causes, at least in the first instance, affect remarkably to the generation of value in non-profit organizations. A case study has also been provided to solve decision making problems under partial information.

Keywords: Worth-creating activities, non-profit organizations, hybrid business, forgotten effects

DOI: 10.3233/JIFS-179628

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Ferrer-Comalat, Joan Carles | Corominas-Coll, Dolors | Linares-Mustaró, Salvador

Article Type: Research Article

Abstract: Models of economic behavior are based on the search for and establishing of relationships between the various economic variables included in the model. Generally speaking, those coefficients that appear in relationships between the model variables are specific values that are determined when the model is to be used to make a given prediction. In this article we propose incorporating fuzzy logic into the study of economic models via the incorporation of fuzzy numbers to express the coefficients relating the different variables. To develop this idea, we analyze a simplified model for determining national income in which it is assumed that, …for the sake of equilibrium, said value is composed of consumption and investment. Also, by relating the consumption function to income, we analyze a relationship model between the variables. To obtain broader and more real information than that resulting from the application of classical models, we incorporate fuzzy logic by assuming the parameters that establish the degree of dependence between the variables to be fuzzy numbers with a known membership function. Depending on their form, we determine their respective membership function for national income. Show more

Keywords: Fuzzy logic, economic models, national income, fuzzy arithmetic, extension principle

DOI: 10.3233/JIFS-179627

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Li, Xiaoping | Tao, Yujie | Li, Yanhong

Article Type: Research Article

Abstract: A polygonal fuzzy numbers can describe fuzzy information by means of finite ordered real numbers. It not only overcomes the complexity of traditional fuzzy number operations, but also keeps some good properties of trapezoidal fuzzy numbers, and it can approximate general fuzzy numbers with arbitrary precision. In this paper, a weighted arithmetic average operator is defined by the ordered representation and its operations of the polygonal fuzzy numbers, and a new Euclidean distance for measuring the polygonal fuzzy numbers is given. Secondly, in view of cost attribute and benefit attributes, the polygonal fuzzy decision matrix is normalized, and the weighted …Euclidean distance is used to solve the positive (negative) ideal solution and the relative closeness of the decision matrix, and then a new decision method is given. Finally, the effectiveness of the proposed decision-making method is illustrated by an example of the evaluation of logistics companies by shopping websites. Show more

Keywords: Polygonal fuzzy number, ordered representation, Euclidean distance, positive (negative) ideal solution, multiple attribute decision making

DOI: 10.3233/JIFS-191588

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Hu, Xiaohan | Jiang, Rong | Shi, Mingyue | Shang, Jingwei

Article Type: Research Article

Abstract: In order to solve the trust problem generated by each node in the medical cloud system during the interaction process, a dynamic access control model based on trust evaluation is proposed in this paper. The model uses entropy weight method and fuzzy theory to fit the comprehensive interaction trust value of nodes, add the role-based two-way selection mechanism and third-party real-time monitoring mechanism for dynamic access control. Give the specific procedures and methods. Through simulation and comparison experiments with the classic Eigen-Trust model and RBAC, we can see that the model proposed in this paper has great advantages in dynamic …controllability, time complexity and trust accuracy. Show more

Keywords: Cloud computing, health care big data, information entropy, trust evaluation, fuzzy relation matrix, access control

DOI: 10.3233/JIFS-191149

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Reig-Mullor, Javier | Brotons-Martinez, Jose M. | Sansalvador-Selles, Manuel E.

Article Type: Research Article

Abstract: In this paper, a novel approach to the bank ranking process based on the possibilistic theory is proposed. Through this new method, the sensitivity of the results can be improved. Several methods are applied in order to rank the financial performance of Spanish Banks. Methods such as the Fuzzy Analytic Hierarchy Process (FAHP) and fuzzy TOPSIS are integrated in the proposed model. Criteria and sub-criteria weights are computed based on the judgments of experts using FAHP. These weights and financial indicators are inputs of the fuzzy TOPSIS methods for ranking the banks. The financial ratios are based on the CAMEL …rating system criteria. Moreover, the results from the application of several distance measurements (Vertex, Hamming and Euclidean) in fuzzy TOPSIS as well as a new measure based on the possibilistic theory are compared. Finally, the results obtained applying fuzzy TOPSIS show that they vary depending on the separate measure, so it is necessary to have different measures to be able to correct decision making. Show more

Keywords: Financial performance, fuzzy numbers, fuzzy AHP, fuzzy TOPSIS, CAMELS rating system

DOI: 10.3233/JIFS-179626

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Hossein-Abad, Hadi Mahdipour | Shabanian, Mohsen | Kazerouni, Iman Abaspur

Article Type: Research Article

Abstract: The conventional fuzzy c-means (FCM) clustering method can be applied on data, where data features are crisp; however, when the features are fuzzy, the conventional FCM cannot be utilized. Recently, some researchers applied FCM on fuzzy numbers when the used metric has a crisp value. Since difference between two fuzzy numbers can be represented by a fuzzy value better than crisp one, in this paper, it is going to extend the FCM method for clustering symmetric triangular fuzzy numbers, where the used metric has a fuzzy value. It will be shown that the proposed fuzzy distance expresses the distance between …two fuzzy numbers much better than crisp metrics. Then the proposed method has been applied on simulated and various real data, where it is compared with several new methods. The experimental results show better performance of the proposed method in compare to other ones. Show more

Keywords: Clustering, fuzzy c-means clustering method, triangular fuzzy number, fuzzy smaller

DOI: 10.3233/JIFS-180971

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Khan, Mudassir | Ansari, Mohd Dilshad

Article Type: Research Article

Abstract: Due to advancement of modern computing technology, software and its products have played an important role in the success and failure of any business. Nowadays, numerous researchers have focused their work on the development of new software quality models and its scopes. Evaluating software quality models based on several attributes is an essential and complex multi-criteria decision making problem (MCDM). To tackle this issue, several studies have been presented for the evaluation of software quality models by utilizing decision making and the idea of fuzzy sets (FSs). Present research develops an intuitionistic fuzzy (IF) improved score function method to deal …with MCDM problems under intuitionistic fuzzy sets (IFSs). Further, the efficiency and feasibility of the proposed method is illustrated to choose the best software quality model under IF environment. To authorize the results, comparative study with previous developed approaches is discussed. Show more

Keywords: Intuitionistic fuzzy sets, divergence measure, MCDM, score function, software quality model

DOI: 10.3233/JIFS-191153

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019