Journal of Intelligent & Fuzzy Systems - Volume 39, issue 3

Authors: Saqib, Muhammad | Akram, Muhammad | Bashir, Shahida

Article Type: Research Article

Abstract: A bipolar fuzzy set model is an extension of fuzzy set model. We develop new iterative methods: generalized Jacobi, generalized Gauss-Seidel, refined Jacobi, refined Gauss-seidel, refined generalized Jacobi and refined generalized Gauss-seidel methods, for solving bipolar fuzzy system of linear equations(BFSLEs). We decompose n  ×  n BFSLEs into 4n  ×  4n symmetric crisp linear system. We present some results that give the convergence of proposed iterative methods. We solve some BFSLEs to check the validity, efficiency and stability of our proposed iterative schemes. Further, we compute Hausdorff distance between the exact solutions and approximate solution of our proposed schemes. The …numerical examples show that some proposed methods converge for the BFSLEs, but Jacobi and Gauss-seidel iterative methods diverge for BFSLEs. Finally, comparison tables show the performance, validity and efficiency of our proposed iterative methods for BFSLEs. Show more

Keywords: Bipolar fuzzy system of linear equations, generalized Jacobi method, generalized Gauss-sediel method, refined generalized Jacobi method, refined generalized Gauss-seidel method

DOI: 10.3233/JIFS-200084

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3971-3985, 2020

Authors: Li, Changqing | Zhang, Yanlan | Zhang, Jing

Article Type: Research Article

Abstract: The idea of statistical convergence, which was first introduced by Fast and Steinhaus independently in 1951, has become one of the most active area of research in the field of mathematics. Recently, it has been applied to the realm of metrics by several authors and some useful results have been obtained. However, the existence of non-completable fuzzy metric spaces, in the sense of George and Veeramani, demonstrates that the theory of fuzzy metrics seem to be richer than that of metrics. In view of this, we attempt to generalize this convergence to the realm of fuzzy metrics. Firstly, we introduce …the concept of sts -convergence in fuzzy metric spaces. Then we characterize those fuzzy metric spaces in which all convergent sequences are sts -convergent. Finally, we study sts -Cauchy sequences in fuzzy metric spaces and sts -completeness of fuzzy metric spaces. Show more

Keywords: Fuzzy metric, statistically convergent sequence, statistically Cauchy sequence, statistical completeness, convergence

DOI: 10.3233/JIFS-200148

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3987-3993, 2020

Authors: Jahan, I. | Manas, A.

Article Type: Research Article

Abstract: In this paper, the concept of a maximal L -subgroup of an L -group has been defined in the spirit of classical group theory. Then, a level subset characterization has been established for the same. Then, this notion of maximal L -subgroups has been used to define Frattini L -subgroup. Further, the concept of non-generators of an L -group has been developed and its relation with the Frattini L -subgroup of an L -group has been established like their classical counterparts. Moreover, several properties pertaining to the concepts of maximal L -subgroups and Frattini L -subgroup have also been investigated. …These two notions have been illustrated through several examples. Show more

Keywords: L-algebra, L-subgroup, generated L-subgroup, normal L-subgroup, maximal L-subgroup, Frattini L-subgroup, non-generators of an L-group

DOI: 10.3233/JIFS-200157

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3995-4007, 2020

Authors: Zahar Djordjevic, Marija | Simeunovic, Barbara | Nestic, Snezana | Aleksic, Aleksandar | Puskaric, Hrvoje

Article Type: Research Article

Abstract: Improvement of the production process presents a very important management task for both researchers and practitioners and enables a better market position of the enterprise. Key Performance Indicators (KPIs) of the production process can provide useful information on the current state of the ongoing process. In this paper, the relative importance of KPIs and their values at the enterprise level were assessed by the experts and decision-makers. Their estimates are described by the linguistic variables which were modeled by intuitionistic fuzzy numbers. The weights vector of KPIs at the level of the considered enterprise is given by the Fuzzy Analytic …Hierarchical Process (FAHP) with Triangular Intuitionistic Fuzzy Numbers (TIFNs). The rank of enterprises with respect to KPIs’ values and their weights was calculated using the modified TOPSIS with TIFNs. The developed model was tested on 30 enterprises from Serbia, belonging to the sector of small and medium-sized (SME) production enterprises. The improvement strategies of KPIs should be proposed at the level of each enterprise, separately, respecting the KPIs’ values of the first-ranked enterprise. Show more

Keywords: Intuitionistic fuzzy numbers, fuzzy AHP, fuzzy TOPSIS, production process, benchmarking

DOI: 10.3233/JIFS-200159

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4009-4026, 2020

Authors: Runkler, Thomas A.

Article Type: Research Article

Abstract: Fuzzy pairwise preferences are an important model to specify and process expert opinions. A fuzzy pairwise preference matrix contains degrees of preference of each option over each other option. Such degrees of preference are often numerically specified by domain experts. In decision processes it is highly desirable to be able to analyze such preference structures, in order to answer questions like: Which objects are most or least preferred? Are there clusters of options with similar preference? Are the preferences consistent or partially contradictory? An important approach for such analysis is visualization. The goal is to produce good visualizations of preference …matrices in order to better understand the expert opinions, to easily identify favorite or less favorite options, to discuss and address inconsistencies, or to reach consensus in group decision processes. Standard methods for visualization of preferences are matrix visualization and chord diagrams, which are not suitable for larger data sets, and which are not able to visualize clusters or inconsistencies. To overcome this drawback we propose PrefMap, a new method for visualizing preference matrices. Experiments with nine artificial and real–world preference data sets indicate that PrefMap yields good visualizations that allow to easily identify favorite and less favorite options, clusters, and inconsistencies, even for large data sets. Show more

Keywords: fuzzy preference relations, visualization, multidimensional scaling

DOI: 10.3233/JIFS-200189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4027-4040, 2020

Authors: Liu, Fang | Tan, Xu | Yang, Hui | Zhao, Hui

Article Type: Research Article

Abstract: Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and …the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs. Show more

Keywords: Decision making, intuitionistic fuzzy preference relation (IFPR), inherent property, approximate consistency, priority vector

DOI: 10.3233/JIFS-200200

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4041-4058, 2020

Authors: Ren, Weina | Li, Chengdong | Wen, Peng

Article Type: Research Article

Abstract: As one kind of readily available renewable energy sources, wind is widely used in power generation where wind speed plays an important role. Generally speaking, we need to forecast the wind speed for improving the controllability of wind power generation. However, there exists considerable randomness and instabilities in wind speed data so that it is difficult to obtain accurate forecasting results. In this paper, we propose a novel fuzzy inference method based hybrid model for accurate wind speed forecasting. In this hybrid model, we adopt two strategies to enhance the estimation performance. On one hand, we propose the purification machine …which utilize the Irregular Information Reduction Module (IIRM) and the Irrelevant Variable Reduction Module (IVRM) to reduce the randomness and instabilities of the data and to eliminate the variables with zero or negative effect in the wind speed time series. On the other hand, we adopt the developed Single-Input-Rule-Modules based Fuzzy Inference System (SIRM-FIS), the functionally weighted SIRM-FIS (FWSIRM-FIS) to realize the prediction of wind speed. This FWSIRM-FIS utilizes the multi-variable functional weights to dynamically measure the importance of the input variables so that the input-output mapping can be strengthened and more accurate forecasting results can be achieved. Furthermore, detailed experiments and comparisons are given. Experimental results demonstrate that the proposed FWSIRM-FIS and purification machine contributes greatly to deal with the randomness and instability in the wind speed data and yield more accurate forecasting results than those existing excellent forecasting models. Show more

Keywords: Fuzzy inference system, purification machine, wind speed forecasting, time series prediction

DOI: 10.3233/JIFS-200205

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4059-4070, 2020

Authors: Mohammadzadeh, E. | Muhiuddin, G. | Zhan, J. | Borzooei, R.A.

Article Type: Research Article

Abstract: In this paper, we introduce a new definition for nilpotent fuzzy Lie ideal, which is a well-defined extension of nilpotent Lie ideal in Lie algebras, and we name it a good nilpotent fuzzy Lie ideal . Then we prove that a Lie algebra is nilpotent if and only if any fuzzy Lie ideal of it, is a good nilpotent fuzzy Lie ideal. In particular, we construct a nilpotent Lie algebra via a good nilpotent fuzzy Lie ideal. Also, we prove that with some conditions, every good nilpotent fuzzy Lie ideal is finite. Finally, we define an Engel fuzzy Lie ideal, …and we show that every Engel fuzzy Lie ideal of a finite Lie algebra is a good nilpotent fuzzy Lie ideal. We think that these notions could be useful to solve some problems of Lie algebras with nilpotent fuzzy Lie ideals. Show more

Keywords: Lie algebra, nilpotent Lie algebra, (good nilpotent) fuzzy Lie ideal

DOI: 10.3233/JIFS-200211

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4071-4079, 2020

Authors: Zhang, Tao | Liu, Meng-Qi | Rong, Mei

Article Type: Research Article

Abstract: Dynamic Concept-cognitive Learning (CCL) is an active field in cognitive computing. Decremented concept cognition is an important topic in dynamic CCL. As an important feature of the dynamic CCL, attenuation characteristics have been successfully visualized by concept lattice and three-dimensional attribute topology. However, the existing attenuation characteristic analysis method has limitations to the description of interaction between attributes. A method of attenuation characteristics analysis of concept tree is proposed. The coupling between nodes is discussed from the concept tree, the nodes are decremented according to the coupling relationship, and the corresponding node attenuation rules are discussed according to the different …types of nodes. In this paper, the news attention is the research object. The experimental results show that the attenuation characteristic analysis scheme of the concept tree is feasible. In the process of attenuation, the effect of attribute attenuation on the concept structure can be clearly demonstrated. At the same time, the concept tree can better visualize the process of decremented news attention than the concept lattice and three-dimensional attribute topology. Show more

Keywords: Concept-cognitive learning, formal concept analysis, concept tree, decremented concept cognition, attenuation characteristics

DOI: 10.3233/JIFS-200218

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4081-4094, 2020

Authors: Bagheri Sanjareh, Mehrdad | Nazari, Mohammad Hassan | Gharehpetian, Gevork B. | Hosseinian, Seyed Hossein

Article Type: Research Article

Abstract: The frequency control of an islanded microgrid is consisted of primary frequency control (PFC) and secondary frequency control (SFC). This paper proposes a novel cooperative application of Battery Energy Storage System (BESS), Photovoltaic (PV) systems and LED lighting loads (LEDLLs) to quickly intercept frequency deviation in the stage of PFC. The slow responding distributed generators handle SFC by restoring the frequency to its nominal value. For participation in PFC, in the case of power shortage, LEDLLs decrease their power consumption, and in the case of power surplus, the PVs decrease their power generation. While PVs and LEDLLs are participating in …PFC with their maximum capability, the BESS frequency controller is tuned to inject/absorb enough power in both cases to keep the frequency within safe limits. In this paper for battery sizing, instead of using its nominal power, a modified overloading capability to fast discharge/charge is used to reduce the required battery size for PFC that also prevents damaging it during fast discharge/charge for PFC. The proposed approach is evaluated on the CIGRE low voltage microgrid using MATLAB/Simulink software. Simulation results show that besides the overloading characteristics, the cooperative utilization of BESS, PVs and LEDLLs also reduce the battery size. Show more

Keywords: Microgrid, Islanded mode, Frequency control, Battery energy storage system, PV, LED lighting loads

DOI: 10.3233/JIFS-200235

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4095-4109, 2020

Authors: Liu, Donghai | Liu, Yuanyuan | Wang, Lizhen

Article Type: Research Article

Abstract: The linguistic q-rung orthopair fuzzy set is a powerful tool in representing linguistic assessments. Considering that the traditional decision making methods cannot deal with the situation that the best choice may not be the minimum or the maximum but between them, we propose an innovative TOPSIS method with linguistic q-rung orthopair fuzzy numbers based on the reference ideal theory. Firstly, the new operations of linguistic q-rung orthopair fuzzy sets are introduced based on the linguistic scale function. In addition, we propose the Minkowski distance measure of linguistic q-rung orthopair fuzzy numbers to make up for the defects of the existing …distance measures based on the linguistic scale function. By using the new operations of linguistic q-rung orthopair fuzzy numbers, we propose the linguistic q-rung orthopair fuzzy weighted averaging operator and the linguistic q-rung orthopair fuzzy weighted geometric operator to aggregate linguistic decision information. Furthermore, we develop a reference ideal TOPSIS method to the linguistic q-rung orthopair fuzzy decision making problems. Finally, an example concerning the postgraduate entrance qualification assessment is given to illustrate the feasibility of the proposed method. Some comparative analysis is also given to show the efficiency of the method, in addition, the sensitivity analysis and stability analysis of the proposed method are also given. Show more

Keywords: Linguistic q-rung orthopair fuzzy numbers, linguistic scale function, distance measure, reference ideal method, TOPSIS method

DOI: 10.3233/JIFS-200244

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4111-4131, 2020

Authors: Samanlioglu, Funda | Ayağ, Zeki

Article Type: Research Article

Abstract: In this study, a hybrid approach is presented for the evaluation and selection of transformers in a power distribution project. Ranking transformers and selecting the best among alternatives is a complex multiple criteria decision making (MCDM) problem with various possibly conflicting quantitative and qualitative criteria. In this research, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy Preference Ranking Organization Method for Enriching Evaluations II (hesitant F-PROMETHEE II) are combined to evaluate and rank transformers. In the hesitant fuzzy AHP-PROMETHEE II, hesitant F-AHP is implemented to determine criteria weights and hesitant F-PROMETHEE II is …applied to rank transformer alternatives, utilizing obtained criteria weights. An illustrative example is presented to demonstrate the effectiveness and applicability of the proposed approach. In the example, five transformers are evaluated based on twelve criteria by three decision makers (DMs) and best alternative is selected. For comparison analysis, integration of hesitant F-AHP and hesitant fuzzy Technique for Order Preference by Similarity to Ideal Solution (hesitant F-TOPSIS) is used and results are compared. Show more

Keywords: Transformer selection, hesitant fuzzy, multiple-criteria decision making, AHP-PROMETHEE II, AHP-TOPSIS

DOI: 10.3233/JIFS-200261

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4133-4145, 2020

Authors: Coutinho, Pedro H.S. | Peixoto, Márcia L.C. | Lacerda, Márcio J. | Bernal, Miguel | Palhares, Reinaldo M.

Article Type: Research Article

Abstract: This paper presents new stability and stabilisation conditions in the form of linear matrix inequalities for discrete-time Takagi-Sugeno fuzzy systems; they are derived considering a class of non-quadratic Lyapunov functions with multi-parametric non-monotonic terms, which significantly enhances the feasibility set of current state-of-the-art results. In addition, extensions to cope with the disturbance attenuation control problem are included. Benchmark numerical examples are provided to illustrate the effectiveness of the proposed approach.

Keywords: Stability analysis, control design, Linear Matrix Inequality, non-quadratic Lyapunov function, non-monotonic functions

DOI: 10.3233/JIFS-200262

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4147-4158, 2020

Authors: Annapandi, P. | Banumathi, R. | Pratheeba, N.S. | Manuela, A. Amala

Article Type: Research Article

Abstract: Due to the intermittent nature of renewable sources, the generation of power is varied which is the main problem in renewable energy system. Miss-matching between the power generation and load power causes a deviation from the desired voltage and frequency in power supply. Therefore, a new efficient smart grid system is required for an optimal power flow management. In this paper, a hybrid approach is presented for power flow management of HRES connected smart grid system. The novelty of the proposed approach is the combined execution of IHHO with SOA named as I2HOSOA technique. In the established work, the HHO …is integrated by crossover and mutation function, it is known as IHHO. The main contribution of the proposed strategy is to control the power flow based on source and load side parameters variations. In the proposed approach, the control signals of the voltage source are developed by the IHHO based on the variety of power exchange between the source and load side. Similarly, the online control signals are located by the SOA procedure by utilizing the parallel execution against the active and reactive power varieties. The multi-objective function is shaped by the grid required active and reactive power varieties created based on accessible source power. Here, the control parameters of the power controller are enhanced by the proposed technique based control models in light of the power flow varieties. The comparison between established and existing methods is analyzed in terms of reactive current injection, grid code, current amplitude limitation control, active power control, zero active power oscillations, and injection of active and reactive power. Furthermore, the statistical evaluation of established, and existing methods of mean, median, and standard deviation, is evaluated. Finally, the proposed model is executed in MATLAB/Simulink working platform and the execution is compared with the existing techniques. Show more

Keywords: Power flow management, proportional integral (PI) controller, unbalanced voltage drops, current injection, statistical analysis

DOI: 10.3233/JIFS-200266

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4159-4181, 2020

Authors: Lin, Fu-Ning | Yu, Guang-Ji | Xue, Guang-Ming | Han, Jiang-Feng

Article Type: Research Article

Abstract:  Crisp antimatroid is a combinatorial abstraction of convexity. It also can be incorporated into the greedy algorithm in order to seek the optimal solutions. Nevertheless, this kind of significant classical structure has inherent limitations in addressing fuzzy optimization problems and abstracting fuzzy convexities. This paper introduces the concept of L -fuzzifying antimatroid associated with an L -fuzzifying family of feasible sets. Several relevant fundamental properties are obtained. We also propose the concept of L -fuzzifying rank functions for L -fuzzifying antimatroids, and then investigate their axiomatic characterizations. Finally, we shed light upon the bijective correspondence between an L -fuzzifying antimatroid …and its L -fuzzifying rank function. Show more

Keywords: Antimatroid, L-fuzzifying antimatroid, L-fuzzifying family of feasible sets, L-fuzzifying rank function

DOI: 10.3233/JIFS-200274

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4183-4196, 2020

Authors: Khan, Waqar | Hila, Kostaq

Article Type: Research Article

Abstract:  We introduce the notion of fuzzy Abel-Grassmann’s hypergroupoid, hypercongruence, fuzzy hypercongruence, fuzzy strong hypercongruence, compatible relations in an Abel-Grassmann’s hypergroupoid. This paper is aimed to study fuzzy hyperideals, smallest fuzzy hyperideals, fuzzy equivalence relations, fuzzy compatible fuzzy strong compatible, fuzzy hypercongruences, fuzzy strong hypercongruences, fuzzy regular, fuzzy strong regular relations and fuzzy hypercongruences in Abel-Grassmann’s hypergroupoids. Characterizations of hypercongruences, their corresponding quotient structure, homomorphisms and an important theorem on embedding Abel-Grassmann’s hypergroupoids by means of fuzzy sets. We show that each hypergroupoid is embedded into a poe -hypergroupoid of all fuzzy subsets of an Abel-Grassmann’s hypergroupoid.

Keywords: Abel-Grassmann’s hypergroupoid, fuzzy equivalence relation, fuzzy hypercongruence, homomorphism, fuzzy strong hypercongruence, cartesian product, regular Abel-Grassmann’s hypergroupoid

DOI: 10.3233/JIFS-200277

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4197-4209, 2020

Authors: Castiblanco, Fabian | Franco, Camilo | Rodríguez, J. Tinguaro | Montero, Javier

Article Type: Research Article

Abstract: This paper proposes a couple of criteria for evaluating the quality and relevance of a fuzzy partition. These criteria are established from a fuzzy classification system and its recursive De Morgan triplet. We propose a comparison process between the classes of a fuzzy partition, based on a translation invariant similarity relation. Therefore a classification process is carried out with the equivalence relations determined by the similarity relation. Such a relation is built on the commutative group structure formed by the elements of the fuzzy classification system. Our approach is illustrated through an example on image analysis by the fuzzy c-means …algorithm. Show more

Keywords: Relevance, fuzzy classification system, translation invariant similarity relation, fuzzy partitions, proximity relations

DOI: 10.3233/JIFS-200286

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4211-4226, 2020

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

Article Type: Research Article

Abstract: Many recent applications such as sensor networks generate continuous and time varying data streams that are often gathered from multiple data sources with some incompleteness and high dimensionality. Clustering such incomplete high dimensional streaming data faces four constraints which are 1) data incompleteness, 2) high dimensionality of data, 3) data distribution, 4) data streams’ continuous nature. Thus, in this paper, we propose the Subspace clustering for Incomplete High dimensional Data streams (SIHD) framework that overcomes the above clustering issues. The proposed SIHD provides continuous missing values imputation for incomplete streams based on the corresponding nearest-neighbors’ intervals. An adaptive subspace clustering …mechanism is proposed to deal with such incomplete high dimensional data streams. Our experimental results using two different data sets prove the efficiency of the proposed SIHD framework in clustering such incomplete high dimensional data streams in terms of accuracy, precision, sensitivity, specificity, and F-score compared to five algorithms GFCM, GBDC-P2P, DS, Ensemble, and DMSC. The proposed SIHD improved: 1) the accuracy on average over the five algorithms in the same mentioned order by 11.3%, 10.8%, 6.5%, 4.1%, and 3.6%, 2) the precision by 15%, 10.6%, 6.4%, 4%, and 3.5%, 3) the sensitivity by 16.6%, 10.6%, 5.8%, 4.2%, and 3.6%, 4) the specificity by 16.8%, 10.9%, 6.5%, 4%, and 3.5%, 5) the F-score by 16.6%, 10.7%, 6.6%, 4.1%, and 3.6%. Show more

Keywords: Data streams, incomplete data imputation, high dimensional data, subspace clustering

DOI: 10.3233/JIFS-200297

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4227-4243, 2020

Authors: Liu, Hongping | Wei, Ruiju | Ge, Qian

Article Type: Research Article

Abstract: By means of a fuzzy binary operation defined on partially ordered sets, a new kind of ordered fuzzy group is proposed in this paper. Some properties of this ordered fuzzy group are studied. Following that, its substructures, such as subgroup and convex subgroup, as well as its homomorphisms, along with their properties are explored. It is shown that each family of these substructures forms a convex structure, where the convex hull of a subset is exactly the (convex) subgroup generated by itself, and the homomorphisms between two ordered fuzzy groups are convexity-preserving mappings between the corresponding convex spaces. In addition, …when these substructures are extended to fuzzy setting, several L -convex structures are constructed and investigated. Show more

Keywords: Fuzzy binary operation, ordered fuzzy group, subgroup, convex structure, convexity-preserving

DOI: 10.3233/JIFS-200311

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4245-4257, 2020

Authors: Shabir, Muhammad | Gul, Rizwan

Article Type: Research Article

Abstract: Bipolar soft sets and rough sets are two different techniques to cope with uncertainty. A possible fusion of rough sets and bipolar soft sets is proposed by Karaaslan and Çağman. They introduced the notion of bipolar soft rough set. In this article, a new technique is being introduced to study roughness through bipolar soft sets. In this new technique of finding approximations of a set, flavour of both theories of bipolar soft set and rough set is retained. We call this new hybrid model modified rough bipolar soft set MRBS-set. Moreover, accuracy measure and roughness measure of modified rough bipolar …soft sets are defined in MRBS-approximation space and its application in multi-criteria group decision making is presented. Show more

Keywords: Rough set, soft set, bipolar soft set, bipolar soft P-rough set, modified rough bipolar soft set, MRBS-approximations

DOI: 10.3233/JIFS-200317

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4259-4283, 2020

Authors: Tao, Ran | Xiao, Fuyuan

Article Type: Research Article

Abstract: Group multi-criteria decision-making (GMCDM) is an important part of decision theory, which is aimed to assess alternatives according to multiple criteria by collecting the wisdom of experts. However, in the process of evaluating, because of the limitation of human knowledge and the complexity of problems, an efficient GMCDM approach under uncertain environment still need to be further explored. Thus, in this paper, a novel GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral is proposed. Firstly, since linguistic Z-numbers performs better in coping with uncertain information, it is used to express the evaluation information. Secondly, TOPSIS, one of …the most useful and systematic multi-criteria decision-making (MCDM) method, is adopted as the framework of the proposed approach. Thirdly, frequently it exists interaction between criteria, so Choquet integral is introduced to capture this kind of influence. What’s more, viewing that decision makers (DMs) show different preferences for uncertainty, the risk preference is regarded as a vital parameter when calculating the score of linguistic Z-numbers. An application in supplier selection is illustrated to demonstrate the effectiveness of the proposed approach. Finally, a further comparison and discussion of the proposed GMCDM method is given. Show more

Keywords: Group multi-criteria decision-making, linguistic Z-numbers, Choquet integral, TOPSIS, risk preference

DOI: 10.3233/JIFS-200318

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4285-4298, 2020

Authors: Hu, Kuang-Hua | Lin, Sin-Jin | Hsu, Ming-Fu | Chen, Fu-Hsiang

Article Type: Research Article

Abstract: This study introduces a dynamic decision architecture that involves three steps for corporate performance forecasting as such bad performance has been widely recognized as the main trigger for a financial crisis. Step-1: performance evaluation and integration; Step-2: forecasting model construction; and Step-3: knowledge generation. First, the decision making trial and evaluation laboratory (DEMATEL) is incorporated with balanced scorecards (BSC) to discover the complicated/intertwined relationships among BSC’s four perspectives. To overcome the problem of BSC that cannot yield a specific direction, the study then employs data envelopment analysis (DEA). Apart from previous studies that utilize an all embracing one-stage model, this …set-up extends it to a two-stage model that calculates the performance scores for each BSC perspective. By doing so, users can realize a company’s weaknesses and strengths and identify possible paths toward efficiency. VIKOR is subsequently used to summarize all scores into a synthesized one. Second, the analyzed outcomes are then fed into random vector functional-link (RVFL) networks to establish the forecasting model. To handle the opaque nature of RVFL, the instance learning method is conducted to extract the implicit decision logics. Finally, the introduced architecture, tested by real cases, offers a promising alternative for performance evaluation and forecasting. Show more

Keywords: Artificial intelligence, decision-making, performance evaluation

DOI: 10.3233/JIFS-200322

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4299-4311, 2020

Authors: Sweatha, A. Anjalin | Pitchai, K. Mohaideen

Article Type: Research Article

Abstract: In cryptography the block ciphers are the mostly used symmetric algorithms. In the existing system the standard S-Box of Advanced Encryption Standard(AES) is performed using the irreducible polynomial equation in table form known as look-up tables(LUTs). For more security purposes, second-order reversible cellular automata based S-box is created. The security aspects of the S-Box used in the AES algorithm are evaluated using cryptographic properties like Strict Avalanche Criteria, Non-Linearity, Entropy, and Common Immunity Bias. The design of S-Box using second-order reversible Cellular Automata is better concerning security and dynamic aspect as compared to the classical S-boxes used Advanced Encryption Standard.

Keywords: Look-up tables, cellular automata, classical S-Box

DOI: 10.3233/JIFS-200326

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4313-4318, 2020

Authors: Zhou, Haibo | Zhang, Chaolong | Tan, Shuaixia | Dai, Yu | Duan, Ji’an | Abdul, Ibrahim Ahmed

Article Type: Research Article

Abstract: The fuzzy operator is one of the most important elements affecting the control performance of interval type-2 (IT2) fuzzy proportional-integral (PI) controllers. At present, the most popular fuzzy operators are product fuzzy operator and min() operator. However, the influence of these two different types of fuzzy operators on the IT2 fuzzy PI controllers is not clear. In this research, by studying the derived analytical structure of an IT2 fuzzy PI controller using typical configurations, it is proved mathematically that the variable gains, i.e., proportional and integral gains of typical IT2 fuzzy PI controllers using the min() operator …are smaller than those using the product operator. Moreover, the study highlights that unlike the controllers based on the product operator, the controllers based on the min() operator have a simple analytical structure but provide more control laws. Real-time control experiments on a linear motor validate the theoretical results. Show more

Keywords: Interval type-2 fuzzy control, proportional-integral (PI) control, fuzzy operator, analytical structure, variable gains

DOI: 10.3233/JIFS-200334

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4319-4329, 2020

Authors: Liu, Baoliang | Zhang, Zhiqiang | Wen, Yanqing | Kang, Shugui | Guo, Yanxin | Qiu, Qingan

Article Type: Research Article

Abstract: Reliability analysis of complex systems subject to competing failure processes based on probability theory has received increasing attention. However, in many situations, the observed data is too limited to estimate the parameters and probability distributions of the system by statistic methods. To address this problem, an uncertain degradation models is proposed in this paper under the framework of uncertainty theory. Based on this model, a complex system which is subject to both continuous internal degradation and external shocks is introduced. The continuous internal degradation of the system is controlled by some uncertain factors, and the external shocks are deemed to …an uncertain renewal reward process. Reliability for the complex systems is obtained by employing the uncertainty theory. Finally, a case study is presented to demonstrate the effectiveness of the results obtained in the paper. Show more

Keywords: Competing failure processes, reliability, uncertainty theory, uncertain variable, uncertain distribution

DOI: 10.3233/JIFS-200343

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4331-4339, 2020

Authors: Wang, Jun Tao | Borzooei, R. A. | Aaly Kologani, M.

Article Type: Research Article

Abstract: In this paper, we characterize the algebraic structure of hoops via stabilizers. First, we further study left and right stabilizers in hoops and discuss the relationship between them. Then, we characterize some special classes of hoops, for example, Wajsberg hoops, local hoops, Gödel hoops and stabilizer hoops, in terms of stabilizers. Finally, we further determine the relationship between stabilizers and filters in hoops and obtain some improvement results. This results also give answer to open problem, which was proposed in [Stabilizers in MTL-algebras, Journal of Intelligent and Fuzzy Systems, 35 (2018) 717-727]. These results will provide a more general algebraic …foundation for consequence connectives in fuzzy logic based on continuous t-norms. Show more

Keywords: 03G25, 13B30, Logical algebra, hoop, stabilizer, sub-summand, Wajsberg hoops, Gödel hoops

DOI: 10.3233/JIFS-200345

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4341-4348, 2020

Authors: Rezaei, Kamran | Rezaei, Hassan

Article Type: Research Article

Abstract: The hesitant fuzzy sets (HFSs) are an extension of the classical fuzzy sets. The membership degree of each element in a hesitant fuzzy set can be a set of possible values in the interval [0,1]. On the other hand, distance and similarity measures are important tools in several applications such as pattern recognition, clustering, medical diagnosis, etc. Hence, numerous studies have focused on investigating distance and similarity measures for HFSs. In this paper, some improved distance and similarity measures are introduced for the HFSs, considering the variation range as a hesitance degree for these sets. Comparing the proposed measures to …some available distance and similarity measures indicated the better results of the proposed measures. Finally, the application of the proposed measures was investigated in the clustering. Show more

Keywords: hesitant fuzzy set, distance measure, similarity measure, pattern recognition, clustering

DOI: 10.3233/JIFS-200364

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4349-4360, 2020

Authors: Karthik, G.M. | Sayeekumar, M. | Kumaravel, R. | Aravind, T.

Article Type: Research Article

Abstract: The main challenge of problem lies in the perception of Cognitive Radio technology is to discover licensed empty spectrum pattern. The efficient model is needed for allocation among licensed and unlicensed users in wireless spectrum to improve the extraction rate and collision rate. To discover the spectrum hole in spectrum paging bands, stirred by FP mining technique proposed an efficient enumeration approach, namely Constraint Based Frequent Periodic Pattern Mining (CBFPP). The proposed algorithm uses TRIE-like data structure with data mining constraints. CBFPP algorithm predicts periodic spectrum occupancy holes in the paging bands. It is shown that CBFPP has a …high prediction accuracy with reasonable time complexity. Experiment with synthetic and real data validate higher prediction accuracy and with reasonable time complexities. The unlicensed user utilizes the predicted spectrum pattern in spectrum usage of channel without significant interference to licensed users. Show more

Keywords: Cognitive radio, data mining, frequent pattern, spectrum occupancy prediction

DOI: 10.3233/JIFS-200368

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4361-4368, 2020

Authors: Zhang, Xinrui | Sun, Bingzhen | Chen, Xiangtang | Chu, Xiaoli | Yang, Jianan

Article Type: Research Article

Abstract: Companies are attaching more and more importance to sustainable supply chain management (SSCM) as which makes the right strategy measures for companies. Due to the complexity of external environmental factors and internal structure, sustainable supply chain management is vulnerable to various risks. The purpose of this paper is to present a new two-stage approach for determining the best practitioner in Iran Pars Special Economic Energy Zone based on the sustainable supply chain risk management (SSCRM). The best and worst method (BWM) is used to determine the weight of risk factors. Then the method of linguistic value soft set is used …to assess the impact of risk factors on each company’s sustainable supply chain which is a multiple attribute decision making problem with language preference in the second stage. Consequently, the ranking results of sustainable supply chain of each enterprise are obtained. This study contributes to finding the key risk factors of SSCRM. Evaluating these companies SSCRM with preference information, the best practitioner can obtain. The combination of BWM and linguistic value soft set approach provides a new nonparametric theoretical method and tool for this kind of decision-making problems with this background. At the same time, the conclusions of this study have guiding significance for the implementation of industrial supply chain. Limitations of the study along with future research directions are also presented. Show more

Keywords: Sustainable, supply chain risk management, BWM, linguistic value soft set

DOI: 10.3233/JIFS-200372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4369-4382, 2020

Authors: Gao, Lunshan

Article Type: Research Article

Abstract: Standard quadratic optimization problems (StQPs) are NP-hard in computational complexity theory when the matrix is indefinite. This paper describes an approximate algorithm of finding inner optimal values of StQPs. The approximate algorithm fuzzifies variable x  ∈ R n with normalized possibility distributions and simplifies the solving of StQPs. The approximation ratio is discussed and determined. Numerical results show that (1) the new algorithm achieves higher accuracy than the semidefinite programming method and linear programming approximation method; (2) the novel algorithm consumes less than one out of fourth computational time that is consumed by linear programming approximation method; (3) the …computational time of the new algorithm does not correlate with the matrix densities whereas the computational times of the branch-and-bound and heuristic algorithms do. Show more

Keywords: Standard quadratic optimization problem, approximation ratio, fuzzification, triangular fuzzy number, normalized possibility distribution

DOI: 10.3233/JIFS-200374

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4383-4392, 2020

Authors: Jia, Wei | Yan, Li | Ma, Zongmin | Niu, Weinan

Article Type: Research Article

Abstract: Influence maximization is a fundamental problem, which is aimed to specify a small number of individuals as seed set to influence the largest number of individuals under a certain influence cascade model. Most existing works on influence maximization may have either high effectiveness or good efficiency,which can not balance both the effectiveness and efficiency. One of the reason is that they do not consider the effect of influence overlap on the effectiveness. That is, these works ignore the phenomenon that the same set of nodes may be influenced by a subset of different influential nodes. To tackle the effectiveness of …heuristic algorithm, we propose a three-phase-based heuristic algorithm, called Three-Phase-based Heuristic (TPH), which uses K-shell method to find influential nodes firstly. Moreover, we utilize weighed degree to make up for the coarse-grained of K-shell method. At last, we take advantage of similarity index to reduce the effect of influence overlap by covering the similar neighbor nodes with low influence. Furthermore, exhaustive experiments indicate that the proposed algorithm outperforms the other baseline algorithms in the aspects of influence spread and running time. Show more

Keywords: Influence maximization, similarity index, influence overlap, social networks

DOI: 10.3233/JIFS-200383

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4393-4403, 2020

Authors: Chung, Yao-Liang | Chung, Hung-Yuan | Tsai, Wei-Feng

Article Type: Research Article

Abstract: In the present study, we sought to enable instant tracking of the hand region as a region of interest (ROI) within the image range of a webcam, while also identifying specific hand gestures to facilitate the control of home appliances in smart homes or issuing of commands to human-computer interaction fields. To accomplish this objective, we first applied skin color detection and noise processing to remove unnecessary background information from the captured image, before applying background subtraction for detection of the ROI. Then, to prevent background objects or noise from influencing the ROI, we utilized the kernelized correlation filters (KCF) …algorithm to implement tracking of the detected ROI. Next, the size of the ROI image was resized to 100×120 and input into a deep convolutional neural network (CNN) to enable the identification of various hand gestures. In the present study, two deep CNN architectures modified from the AlexNet CNN and VGGNet CNN, respectively, were developed by substantially reducing the number of network parameters used and appropriately adjusting internal network configuration settings. Then, the tracking and recognition process described above was continuously repeated to achieve immediate effect, with the execution of the system continuing until the hand is removed from the camera range. The results indicated excellent performance by both of the proposed deep CNN architectures. In particular, the modified version of the VGGNet CNN achieved better performance with a recognition rate of 99.90% for the utilized training data set and a recognition rate of 95.61% for the utilized test data set, which indicate the good feasibility of the system for practical applications. Show more

Keywords: Deep CNN, gesture recognition, VGGNet, AlexNet

DOI: 10.3233/JIFS-200385

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4405-4418, 2020

Authors: Liu, Shiqin | Liu, Liying | Wang, Na | Zhang, Jianguang

Article Type: Research Article

Abstract: Under the axiom system of uncertainty theory, the paper mainly introduce the new definition of the pth moment exponential stability for uncertain differential equation with jumps. For illustrating the concept, some examples and counterexamples are given. Furthermore, we obtain a necessary and sufficient condition of stability in pth moment exponential for the linear uncertain differential equation with jumps. Also, the conclusion condition is illustrated very clearly by two examples.

Keywords: Stability, uncertain differential equation, uncertainty theory

DOI: 10.3233/JIFS-200409

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4419-4425, 2020

Authors: Xu, Bin

Article Type: Research Article

Abstract: The concept of fuzzy number intuitionistic fuzzy sets (FNIFSs) is designed to effectively depict uncertain information in decision making problems which fundamental characteristic of the FNIFS is that the values of its membership function and non-membership function are depicted with triangular fuzzy numbers (TFNs). The dual Hamy mean (DHM) operator gets good performance in the process of information aggregation due to its ability to capturing the interrelationships among aggregated values. In this paper, we used the dual Hamy mean (DHM) operator and dual weighted Hamy mean (WDHM) operator with fuzzy number intuitionistic fuzzy numbers (FNIFNs) to propose the fuzzy number …intuitionistic fuzzy dual Hamy mean (FNIFDHM) operator and fuzzy number intuitionistic fuzzy weighted dual Hamy mean (FNIFWDHM) operator. Then the MADM methods are proposed along with these operators. In the end, we utilize an applicable example for computer network security evaluation to prove the proposed methods. Show more

Keywords: Multiple attribute decision making (MADM), dual weighted hamy mean (WDHM) operator, fuzzy number intuitionistic fuzzy weighted dual hamy operators (FNIFWDHM), computer network security evaluation

DOI: 10.3233/JIFS-200414

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4427-4441, 2020

Authors: Wang, Xiao | Peng, Zhen

Article Type: Research Article

Abstract: Uncertain pantograph differential equations are an important class of pantograph differential equations driven by uncertain process. This paper investigates two types of stability, namely stability in mean and almost sure stability, for uncertain pantograph differential equations. In detail, the concepts of stability in mean and almost sure stability for uncertain pantograph differential equations are presented. Moreover, we reveal the sufficient conditions for uncertain pantograph differential equations being stable in mean and stable almost surely. Finally, this paper attempts to explore the relationships among stability in mean, almost sure stability as well as stability in measure.

Keywords: Uncertain pantograph differential equation, stability in mean, almost sure stability, uncertainty theory

DOI: 10.3233/JIFS-200426

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4443-4452, 2020

Authors: Wang, Yuanyuan | Li, Xiang | Jiang, Mingxin | Zhang, Haiyan | Tang, E

Article Type: Research Article

Abstract: At present, supervised person re-identification method achieves high identification performance. However, there are a lot of cross cameras with unlabeled data in the actual application scenarios. The high cost of marking data will greatly reduce the effect of the supervised learning model transferring to other scene domains. Therefore, unsupervised learning of person re-identification becomes more attractive in the real world. In addition, due to changes in camera angle, illumination and posture, the extracted person image representation is generally different in the non-cross camera view, but the existing algorithm ignores the difference among cross camera images under camera parameters and environments. …In order to overcome the above problems, we propose unsupervised person re-identification metric learning method. The model learns a shared space to reduce the discrepancy under different cameras. The graph convolution network is further employed to cluster the cross-view image features extracted from the shared space. Our model improves the scalability of pedestrian re-identification in practical application scenarios. Extensive experiments on four large-scale person re-identification public datasets have been conducted to demonstrate the effectiveness of the proposed model. Show more

Keywords: Person re-identification, unsupervised, clustering, graph convolution network, cross-view

DOI: 10.3233/JIFS-200435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4453-4462, 2020

Authors: Deli, Irfan | Long, Hoang Viet | Son, Le Hoang | Kumar, Raghvendra | Dey, Arindam

Article Type: Research Article

Abstract: Soft set is the power tool to deal with uncertainty in a parametric manner. In applications of soft set, one of the most important steps is to define mappings on soft sets. In this study, we model theory of game under theory of soft set which is an effective tool for handling uncertainties events and problems that may exist in a game. To this end, we first define some expected impact functions of players in soft games. Then, we propose three new decision making algorithms to solve the 2.2 × p , 2 . n  × p and m  . 2 × p soft matrix games, …which cannot be settled by the relevant soft methods such as saddle points, lover and upper values, dominated strategies and Nash equilibrium. The proposed soft game algorithms are illustrated by examples. Show more

Keywords: Soft sets, soft games, impact functions, soft payoff, probabilistic solution methods

DOI: 10.3233/JIFS-200440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4463-4472, 2020

Authors: Afzaal, Muhammad Umar | Sajjad, Intisar Ali | Khan, Muhammad Faisal Nadeem | Haroon, Shaikh Saaqib | Amin, Salman | Bo, Rui | ur Rehman, Waqas

Article Type: Research Article

Abstract: The characterization of electrical demand patterns for aggregated customers is considered as an important aspect for system operators or electrical load aggregators to analyze their behavior. The variation in electrical demand among two consecutive time intervals is dependent on various factors such as, lifestyle of customers, weather conditions, type and time of use of appliances and ambient temperature. This paper proposes an improved methodology for probabilistic characterization of aggregate demand while considering different demand aggregation levels and averaging time step durations. At first, a probabilistic model based on Weibull distribution combined with generalized regression neural networks (GRNN) is developed to …extract the inter-temporal behavior of demand variations and, then, this information is used to regenerate aggregate demand patterns. Average Mean Absolute Percentage Error (AMAPE) is used as a statistical indicator to assess the accuracy and effectiveness of proposed probabilistic modeling approach. The results have demonstrated that the performance of proposed approach is better in comparison with an existing Beta distribution-based method to characterize aggregate electrical demand patterns. Show more

Keywords: Electrical demand characterization, generalized regression neural networks, scenario generations, time series, Weibull probability distribution

DOI: 10.3233/JIFS-200462

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4491-4503, 2020

Authors: Dong, Guishan | Mu, Xuewen

Article Type: Research Article

Abstract: The support vector machine is a classification approach in machine learning. The second-order cone optimization formulation for the soft-margin support vector machine can ensure that the misclassification rate of data points do not exceed a given value. In this paper, a novel second-order cone programming formulation is proposed for the soft-margin support vector machine. The novel formulation uses the l 2 -norm and two margin variables associated with each class to maximize the margin. Two regularization parameters α and β are introduced to control the trade-off between the maximization of margin variables. Numerical results illustrate that the proposed …second-order cone programming formulation for the soft-margin support vector machine has a better prediction performance and robustness than other second-order cone programming support vector machine models used in this article for comparision. Show more

Keywords: Support vector machine, second-order cone programming, binary data classification

DOI: 10.3233/JIFS-200467

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4505-4513, 2020

Authors: Atef, Mohammed | Khalil, Ahmed Mostafa | Li, Sheng-Gang | Azzam, A.A. | El Atik, Abd El Fattah

Article Type: Research Article

Abstract: In this paper, we generalize three types of rough set models based on j -neighborhood space (i.e, type 1 j -neighborhood rough set, type 2 j -neighborhood rough set, and type 3 j -neighborhood rough set), and investigate some of their basic properties. Also, we present another three types of rough set models based on j -adhesion neighborhood space (i.e, type 4 j -adhesion neighborhood rough set, type 5 j -adhesion neighborhood rough set, and type 6 j -adhesion neighborhood rough set). The fundamental properties of approximation operators based on j -adhesion neighborhood space are established. The relationship between the …properties of these types is explained. Finally, according to j -adhesion neighborhood space, we give a comparison between the Yao’s approach and our approach. Show more

Keywords: Rough sets, lower and upper approximations, j-neighborhood, j-adhesion neighborhood, accuracy measure

DOI: 10.3233/JIFS-200482

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4515-4531, 2020

Authors: Moreno, Jenny | Sánchez, Juan | Espitia, Helbert

Article Type: Research Article

Abstract: Floods are a climatic phenomena that affect different regions worldwide and that produces both human and material losses; for example in 2017, six of the worst floods were the cause of 3.273 deaths worldwide. In Colombia, the strong winter wave presented between 2010 and 2011, caused 1,374 deaths and 1,016 missing persons. The main river in Colombia is the Magdalena, which provides great benefits to the country but is also susceptible to flooding. This article presents a proposal to optimize a fuzzy system to prevent flooding in homes adjacent to areas of risk to the Magdalena River. The method used …is based on evolutionary algorithms to perform a global search, including a gradient-based algorithm to improve the solution obtained. The best result achieved was the Mean Square Error (MSE) of 7, 83E  - 05. As a conclusion, it is needed to employ optimization methods for the adjustment of parameters of the fuzzy system when considering that the sets and the rules are systematically obtained. Show more

Keywords: Artificial intelligence, fuzzy model, magdalena river, flood control, climate variability, genetic algorithms, particle swarm

DOI: 10.3233/JIFS-200486

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4533-4546, 2020

Authors: Yu, Wen | Vega, Francisco

Article Type: Research Article

Abstract:  The data driven black-box or gray-box models like neural networks and fuzzy systems have some disadvantages, such as the high and uncertain dimensions and complex learning process. In this paper, we combine the Takagi-Sugeno fuzzy model with long-short term memory cells to overcome these disadvantages. This novel model takes the advantages of the interpretability of the fuzzy system and the good approximation ability of the long-short term memory cell. We propose a fast and stable learning algorithm for this model. Comparisons with others similar black-box and grey-box models are made, in order to observe the advantages of the proposal.

Keywords: LSTM, fuzzy neural networks, nonlinear system identification

DOI: 10.3233/JIFS-200491

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4547-4556, 2020

Authors: Türk, Abdullah | Özkök, Murat

Article Type: Research Article

Abstract: The shipyard facility location selection (FLS) decision is a critical process that involves conflicting, qualitative, and quantitative criteria. Multi-Attribute Decision Making (MADM) methods are used as a powerful tool to overcome this complex problem. Today, using these methods in an integrated way, more accurate, efficient, and systematic results are obtained in solving complex issues such as FLS, which contains an uncertain structure. This paper proposes a framework for the weighting of criteria and ranking potential feasible locations (alternatives) using the combination of fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) methods. …While fuzzy AHP determines the importance values of the criteria by pairwise comparisons, fuzzy TOPSIS prioritizes the alternatives using the relative weights obtained with Fuzzy AHP. The integration of these two techniques provides a robust approach considering the results obtained for the shipyard FLS decision. The applicability of the proposed method is expressed in Turkey by a case study of the shipyard FLS decision. Show more

Keywords: Shipyard, location selection, fuzzy AHP, fuzzy TOPSIS

DOI: 10.3233/JIFS-200522

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4557-4576, 2020

Authors: Liu, Zhenhua | Zhang, Mengting | Li, Yupeng | Chu, Xuening

Article Type: Research Article

Abstract: The evolution of the product family is the essential driving force for the development of a complex product. Only customer satisfaction is emphasized in the traditional module configuration methods, which is not beneficial for product family evolution that is due to non-customer factors such as the emergence of new technology. In this study, the intuitionistic fuzzy number is employed to quantify the degree of correlation between each module and configuration targets, namely customer satisfaction and the degree of evolution of the product family, respectively. The bi-objective integer programming model is constructed by maximizing the degree of customer satisfaction and product …family evolution. An improved Pareto ant colony optimization (P-ACO) is designed to solve this model and subsequently the Pareto frontier is obtained. The radar chart is adopted to represent the performance of each configuration scheme in the Pareto frontier. The feasibility and effectiveness of the proposed method are expounded by a case study and result comparison, showing that this method can provide a more competitive product configuration scheme to customers in the future market. Show more

Keywords: Product family evolution, complex products, module configuration, customer requirements, P-ACO

DOI: 10.3233/JIFS-200527

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4577-4595, 2020

Authors: Rajpoot, Vikram | Mannepalli, Praveen Kumar | Choubey, Shruti Bhargava | Sohoni, Parag | Chaturvedi, Prashant

Article Type: Research Article

Abstract: Image enhancement (IE) is a common thing we use to get better results from previous imagery. This image enhancement is not only used by us, but it is implemented in many fields. Such as implementation in the military field, medical field, legal field, industry field, entertainment field, and much more. The main use of IE in each field is to get clear information. Pedestrian detection is an essential way of support in current traffic management. Traditional pedestrian detection error & miss detection rates are high owing to irregular lighting, dim tunnel atmosphere, and blurred controlled picture, making subsequent identifying hard. …A rapid image enhancement (FIE) algorithm founded on picture model restriction is therefore suggested in this document and reduced to the pedestrian region of interest (ROI) in the pavement close the road under highway tunnel (HT) scene. First, the technique used to assess the local atmospheric light (LAL) by combining global atmospheric light (GAL) and partitioned atmospheric light (AL). Second, the transmission is predicted to be founded on the plan obtained as of the image model’s constraints. The third is for balancing tunnel illumination, the technique utilizes steady instead of illumination. Lastly, the picture of the tunnel is improved by the picture model. Moreover, we propose a narrowing region approach for improving the overall computing performance, due to the real-time requirements of the algorithm. Taking account of the highway tunnel features, which are a blurred scene and difficult to identify from the context, we use a multi-function integration approach to detect the enhanced image. We described a novel filter in this article that is commonly used in computer vision & graphics. Guided algorithm filter is MATLAB simulated. Results of the experimental and comparative assessment indicate that the suggested technique can quickly and efficiently enhance the picture of the tunnel and highly enhance the impact of pedestrian detection. Show more

Keywords: Image enhancement, transmission, atmospheric light, pedestrian detection, constraint of imaging model

DOI: 10.3233/JIFS-200551

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4597-4616, 2020

Authors: Gao, Chengrui | Liu, Feiqiang | Yan, Hua

Article Type: Research Article

Abstract: Infrared and visible image fusion refers to the technology that merges the visual details of visible images and thermal feature information of infrared images; it has been extensively adopted in numerous image processing fields. In this study, a dual-tree complex wavelet transform (DTCWT) and convolutional sparse representation (CSR)-based image fusion method was proposed. In the proposed method, the infrared images and visible images were first decomposed by dual-tree complex wavelet transform to characterize their high-frequency bands and low-frequency band. Subsequently, the high-frequency bands were enhanced by guided filtering (GF), while the low-frequency band was merged through convolutional sparse representation and …choose-max strategy. Lastly, the fused images were reconstructed by inverse DTCWT. In the experiment, the objective and subjective comparisons with other typical methods proved the advantage of the proposed method. To be specific, the results achieved using the proposed method were more consistent with the human vision system and contained more texture detail information. Show more

Keywords: image fusion, dual-tree complex wavelet transform, convolutional sparse representation, guided filter

DOI: 10.3233/JIFS-200554

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4617-4629, 2020

Authors: Zhou, Xiao-Yu | Wang, Xiao-Kang | Wang, Jian-qiang | Li, Jun-Bo | Li, Lin

Article Type: Research Article

Abstract: With the rapid growth of the global population and economy, energy consumption and demad are increasing sharply. As an essential renewable energy, biomass energy can promote the reform of energy production and consumption. Considering the characteristics of long investment cycle and large investment scale of agroforestry biomass power generation (AFBPG) projects, this study establishes a decision support framework for risk ranking of AFBPG project under picture fuzzy environment. The proposed framework considers not only the fuzziness and uncertainty of decision-making problems but also the decision-makers’ (DMs) psychological behavior. First, given the integrity of information representation, DMs provide risk assessment information …expressed with picture fuzzy numbers, and then gives the distance of the picture fuzzy set (PFS) to maximize the PFS information. Second, the entropy weight method is used to compute the objective weight. Third, the VIKOR (Vlse Kriterijumska Optimizacija I Kompromisno Resenje ) – TODIM (an acronym in Portuguese for an interactive multi-criteria decision making) method is suggested for ranking risk factors, which reflects the behavioral psychology of DMs. Moreover, the proposed evaluation model is successfully applied in a practical case. The results show that the model is valid for ranking risk factors under picture fuzzy environment. Last but not least, comparison and sensitivity analysis are implemented to verify the effectiveness and applicability of the proposed method and some suggestions for practical application are put forward. Show more

Keywords: Multi-criteria decision-making, picture fuzzy set, agroforestry biomass power generation project, risk ranking, VIKOR, TODIM

DOI: 10.3233/JIFS-200575

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4631-4650, 2020

Authors: Patro, Sunkuru Gopal Krishna | Mishra, Brojo Kishore | Panda, Sanjaya Kumar | Kumar, Raghvendra | Long, Hoang Viet | Tuan, Tran Manh

Article Type: Research Article

Abstract: A recommender system (RS) delivers personalized suggestions on products based on the interest of a particular user. Content-based filtering (CBF) and collaborative filtering (CF) schemes have been previously used for this task. However, the main challenge in RS is cold start problem (CSP). This originates once a new user joins the system which makes the recommendation task tedious due to the shortage of information (clickstream, dwell time, rating, etc.) regarding the user’s interest. Therefore, CBF and CF are combined together by developing a knowledge-based preference learning (KBPL) system. This system considers the demographic data that includes gender, occupation, and age …for the recommendation task. Initially, the dataset is clustered using the self-organizing map (SOM) technique, then the high dimensional data is decomposed by higher-order singular value decomposition (HOSVD) and finally, Adaptive neuro-fuzzy inference system (ANFIS) predicts the output. For the big dataset, SOM is a robust clustering method and the similarities among the users can be easily observed by grid clustering. The HOSVD extracts the required information from the available data set to find the user similarity by decomposing the dataset in lower dimensions. ANFIS uses IF-THEN rules to recommend similar product to the new users. The proposed KBPL system is evaluated with the Black Friday dataset and the obtained error value is compared with the existing CF and CBF techniques. The proposed KBPL system has obtained root mean squared error (RMSE) of 0.71%, mean absolute error (MAE) of 0.54%, and mean absolute percentage error (MAPE) of 37%. Overall, the outcome of the comparative analysis shows minimum error and better performance in terms of precision, recall, and f-measure for the proposed KBPL system compared to the existing techniques and therefore more suitable for accurately recommending the products for the new users. Show more

Keywords: Clustering, ANFIS, cold start: Data decomposition, prediction, recommendation

DOI: 10.3233/JIFS-200595

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4651-4665, 2020

Authors: Fan, Changxing | Fan, En | Chen, Jihong | Ye, Jun | Zhou, Kang

Article Type: Research Article

Abstract: Port as an irreplaceable important node in the process of logistics is a special form of the integrated logistics system, which completes the basic logistics service and value-added services in the global supply chain logistics system. At present, the port logistics service has become an important breakthrough in the competition of ports, the improvement of port logistics competitiveness has great influence on the development of port and port city and even the area economic development. Analyzing from the port logistics competitiveness, this paper establishes a comprehensive evaluation index system and proposes a single-value neutrosophic cosine measure method to evaluate the …port logistics competitiveness of five sample ports, and gets the score sorting of the logistics competitiveness of these five ports. This method as a helpful tool is clear and easy for port logistics competitiveness evaluation during actual application. Show more

Keywords: Single-valued neutrosophic set (SVNS), port logistics competitiveness, cosine measure, single-value neutrosophic cosine measure method

DOI: 10.3233/JIFS-200598

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4667-4675, 2020

Authors: Ding, Weimin | Wu, Shengli

Article Type: Research Article

Abstract: Stacking is one of the major types of ensemble learning techniques in which a set of base classifiers contributes their outputs to the meta-level classifier, and the meta-level classifier combines them so as to produce more accurate classifications. In this paper, we propose a new stacking algorithm that defines the cross-entropy as the loss function for the classification problem. The training process is conducted by using a neural network with the stochastic gradient descent technique. One major characteristic of our method is its treatment of each meta instance as a whole with one optimization model, which is different from some …other stacking methods such as stacking with multi-response linear regression and stacking with multi-response model trees. In these methods each meta instance is divided into a set of sub-instances. Multiple models apply to those sub-instances and each for a class label. There is no connection between different models. It is very likely that our treatment is a better choice for finding suitable weights. Experiments with 22 data sets from the UCI machine learning repository show that the proposed stacking approach performs well. It outperforms all three base classifiers, several state-of-the-art stacking algorithms, and some other representative ensemble learning methods on average. Show more

Keywords: Ensemble learning, stacking, cross entropy, gradient descent

DOI: 10.3233/JIFS-200600

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 4677-4688, 2020