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