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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Wang, Weizhong | Ma, Yilin | Liu, Shuli
Article Type: Research Article
Abstract: Current risk prioritization approaches for FMEA models are insufficient to cope with risk analysis problem in which the self-confidence of expert’s judgment and the deviation among risk evaluation information are considered, simultaneously. Therefore, to remedy this limitation, this paper reports an extended risk prioritization approach by integrating the MULTIMOORA approach, Z-numbers and power weighted average (PWA) operator. Firstly, the Z-numbers with triangular fuzzy numbers are applied to reflect the self-confidence and uncertainty of expert’s judgment. Next, the PWA operator for Z-numbers (Z-PWA) with similarity measure is proposed to obtain the group risk evaluation matrix by considering the influence of the …deviation among risk evaluation information. Then, an extended version of MULTIMOORA method with developed entropy method is presented to calculate risk priority ranking order of each failure. Finally, the equipment failures in a certain oil and gas plant is utilized to test the extended risk prioritization approach for FMEA model. After that, the sensitivity and comparison studies are led to illustrate the availability and reliability of the proposed risk prioritization approach for FMEA based risk analysis problem. Show more
Keywords: Failure model and effect analysis, risk prioritization, Z-numbers, MULTIMOORA
DOI: 10.3233/JIFS-200678
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2523-2537, 2021
Authors: Zhang, Qiao | Cheng, Xiaoliang | Liao, Shaoyi
Article Type: Research Article
Abstract: Hybrid energy storage system supplies a feasible solution to battery peak current reduction by introducing supercapacitor as auxiliary energy source. Energy management control strategy is a key technology for guaranteeing performance. In this paper, we describe a predictive energy management strategy for battery and supercapacitor hybrid energy storage systems of pure electric vehicles. To utilize the supercapacitor reasonably, Markov chain model is proposed to predict the future load power during a driving cycle. The predictive results are subsequently used by power distribution strategy, which is designed using a low-pass filter and a fuzzy logic controller. The strategy model is developed …under MATLAB/Simulink software environment. To validate the performance of the proposed control strategy, a comparison test is implemented based on a 72 V rated voltage hybrid energy storage system experimental platform. The results indicate that the battery peak currents by proposed predictive control strategy are reduced by 26.32%, 28.21% and 27.12% under the UDDS, SC03 and NEDC three driving cycles respectively. Show more
Keywords: Electric vehicle, hybrid energy storage system, predictive energy management strategy, markov chain
DOI: 10.3233/JIFS-200934
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2539-2549, 2021
Authors: Wang, Zuli | Chiong, Raymond | Fan, Zongwen
Article Type: Research Article
Abstract: Malicious web domains represent a serious threat to online users’ privacy and security, causing monetary loss, theft of private information, and malware attacks, among others. In recent years, machine learning methods have been widely used as prediction models to identify malicious web domains. In this study, we propose a Fuzzy-Weighted Least Squares Support Vector Machine (FW-LS-SVM) model for malicious web domain identification. In our proposed model, a fuzzy-weighted operation is applied to each data sample considering the fact that different samples may have different importance. This fuzzy-weighted operation is also able to alleviate the influence of noise data and improve …the model’s robustness by assigning weights to error constraints. For comparison purposes, three commonly used single machine learning classifiers and three widely used ensemble models are included in our experiments, in order to assess the performance of our proposed FW-LS-SVM and its ensemble version. Hyperlink indicators and uniform resource locator-based features are used to train the prediction models. Experimental results show that our proposed approach is highly effective in identifying malicious web domains, outperforming the well-established single and ensemble models being compared. Show more
Keywords: Malicious web domain identification, support vector machines, fuzzy weights, online attacks
DOI: 10.3233/JIFS-200943
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2551-2559, 2021
Authors: Liu, Peide | Hendalianpour, Ayad
Article Type: Research Article
Abstract: Financial flows are one of the three majors in a Supply Chain (SC). Ignoring financial flows, regardless of the quality of freight transport and information, could lead the organization to a state of bankruptcy, which is a situation directly resulting from a lack of control over financial inputs/outputs. This study proposes a multi-product mathematical model, which makes it possible to choose among suppliers, manufacturing sites, distribution centres, retailers, and transportation vehicles. The purpose of the model is to integrate physical and material dimensions to maximize net corporate profits through inbound and outbound financial flows; it involves payment mechanisms between the …financial and physical flows through maximizing the cash flows of manufacturing sites and suppliers, as two conflicting objectives that must consider the reciprocal effects of their decisions. These objectives are calculated by subtracting costs from the revenue; this process, of course, will ultimately result in an optimization of the organization’s financial flow. To solve the proposed mathematical model, the study relies on two algorithms, namely Particle Swarm Optimization (PSO) and Imperialist Competition Algorithm (ICA). The sample under investigation is solved separately using the three algorithms, and results are then compared. The observations of the study reveal the better performance of PSO. Show more
Keywords: Supply chain financial flow, inbound and outbound flow, mathematical modeling, particle swarm optimization, imperialist competitive algorithm
DOI: 10.3233/JIFS-201068
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2561-2579, 2021
Authors: Kişi, Ömer
Article Type: Research Article
Abstract: Statistical convergence of sequences has been studied in neutrosophic normed spaces (NNS) by Kirişci and Şimşek [39 ]. Ideal convergence is more general than statistical convergence for sequences. This has motivated us to study the ideal convergence in NNS. In this paper, we study the concept of ideal convergence and ideal Cauchy for sequences in NNS.
Keywords: Neutrosophic normed spaced, ideal convergence, ideal Cauchy sequence, t-norm, t-conorm
DOI: 10.3233/JIFS-201568
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2581-2590, 2021
Authors: Yılmaz, Melike | Atan, Tankut
Article Type: Research Article
Abstract: As the Covid-19 pandemic also proved, access to health care plays a crucial role in our lives. Public officials, managers and investors should consider many criteria such as public infrastructure, environment, accessibility and demand for selecting the most appropriate site for a new hospital. Thus, the hospital site selection problem is a critical multi-criteria decision-making (MCDM) problem. This paper is a case study for İstanbul where a recent MCDM methodology, the fuzzy Evaluation based on Distance from Average Solution (EDAS) method, is applied to this problem for the first time. We used a comprehensive set of five main criteria and …17 sub-criteria found in the relevant literature regarding hospital site selection. These criteria were evaluated by three decision-makers to choose the hospital site from three districts. The recommendation of the fuzzy EDAS method was then compared to the outcome of a frequently used fuzzy MCDM method. The methods resulted in different site recommendations. Show more
Keywords: Hospital site selection, health care planning, multi-criteria decision making, fuzzy EDAS, fuzzy TOPSIS
DOI: 10.3233/JIFS-201757
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2591-2602, 2021
Authors: Liu, Xiang-Min | Hu, Jian | Mwakapesa, Deborah Simon | Nanehkaran, Y.A. | Mao, Yi-Min | Zhang, Rui-Peng | Chen, Zhi-Gang
Article Type: Research Article
Abstract: Deep convolutional neural networks (DCNNs), with their complex network structure and powerful feature learning and feature expression capabilities, have been remarkable successes in many large-scale recognition tasks. However, with the expectation of memory overhead and response time, along with the increasing scale of data, DCNN faces three non-rival challenges in a big data environment: excessive network parameters, slow convergence, and inefficient parallelism. To tackle these three problems, this paper develops a deep convolutional neural networks optimization algorithm (PDCNNO) in the MapReduce framework. The proposed method first pruned the network to obtain a compressed network in order to effectively reduce redundant …parameters. Next, a conjugate gradient method based on modified secant equation (CGMSE) is developed in the Map phase to further accelerate the convergence of the network. Finally, a load balancing strategy based on regulate load rate (LBRLA) is proposed in the Reduce phase to quickly achieve equal grouping of data and thus improving the parallel performance of the system. We compared the PDCNNO algorithm with other algorithms on three datasets, including SVHN, EMNIST Digits, and ISLVRC2012. The experimental results show that our algorithm not only reduces the space and time overhead of network training but also obtains a well-performing speed-up ratio in a big data environment. Show more
Keywords: DCNN, MapReduce, network compression, conjugate gradient method, load balancing
DOI: 10.3233/JIFS-201790
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2603-2615, 2021
Authors: Kurt, Mahmut Mahir | Yazıcıoğlu, Osman
Article Type: Research Article
Abstract: Retail e-commerce has been growing over the years by attracting entrepreneurs’ attention. Increasing interest in retail e-commerce has affected competition and made it necessary to choose the right competition strategy. This study aims at selecting the right competition strategy to be successful in retail e-commerce under vague and imprecise conditions. AHP and TOPSIS methods are used under intuitionistic fuzzy environment, which allows decision-makers to reflect their hesitation in their judgements. After a literature review on retail, e-commerce, and competition strategy, the main criteria and sub-criteria of multicriteria retail e-commerce alternative selection are presented. Cost leadership, differentiation, and focusing strategies are …evaluated as competitive strategies, based on the opinions of experts collected through a questionnaire. The results of the study show that the strategies are ranked as differentiation, focus, and cost leadership strategies, respectively. Show more
Keywords: Decision making, intuitionistic fuzzy, competitive strategy, retail, e-commerce
DOI: 10.3233/JIFS-202010
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2617-2637, 2021
Authors: Fu, Wenqing | Khalil, Ahmed Mostafa
Article Type: Research Article
Abstract: In this paper, we will propose the novel notion of neighborhood rough sets on a universe set and study some of their basic properties. Then, the relationships between the neighborhood rough sets and covering rough sets are established. Further, the several related notions of probabilistic neighborhood rough sets are investigated and their basic theoretical are discussed. In addition, the notion of neighborhood rough sets over two different universes is defined, and interesting in their properties are explained. Depend on the neighborhood rough sets over two different universes, two algorithms are designed to solve the rough decision-making problems and clarify their …applicability by two illustrative examples, respectively. Finally, a comparison between Liu et al.’s approach and our approach is given. Show more
Keywords: Rough sets, covering rough sets, neighborhood operator, probabilistic neighborhood rough sets, gradedn-neighborhood rough sets, decision-making
DOI: 10.3233/JIFS-202081
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2639-2664, 2021
Authors: Namarta, | Kaur, Parmpreet | Gupta, Umesh Chandra
Article Type: Research Article
Abstract: In the word of uncertain competitive situations everything is in the state of flux. Under such situations knowing the exact outcomes of mixed strategies adopted by a player is nearly impossible. It is highly rational to assume that no two experts will project the similar fuzzy payoffs for mix of strategies used. Aggregation of expert’s judgement becomes utmost important before solving such competitive situations. Considering this the present paper proposes a method to solve intuitionistic fuzzy game problems by using aggregation operators on payoff judgments of more than one expert. The proposed method significantly adds to the existing literature by …overcoming the limitation of Li’s existing method that considers only one expert’s opinion for solving intuitionistic fuzzy game problems. Illustrative example has been given for showing the superiority of the proposed method. Show more
Keywords: Aggregation operators, intuitionistic fuzzy sets, fuzzy matrix game
DOI: 10.3233/JIFS-202232
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2665-2674, 2021
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