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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: Jiang, Zhibin | Zhou, Jie | Zhang, Yuanpeng | Wang, Shitong
Article Type: Research Article
Abstract: Since the density distribution of each view, which can be often built only from the corresponding partial data observed along each view from the whole face data, ignores the coherent information between all the views, multi-view face recognition sometimes is seriously troubled by an unavoidable phenomenon that the dissimilarity between the samples from the same class but different views is greater than that between the samples from the different classes of same view. In this study, by considering a common hidden space cross all the views, consistent hidden density distribution between views in the common hidden space is delved so …as to address this issue. Accordingly, a novel multi-view support vector machine based on consistent hidden density distributions between views in common hidden space (2V-SVM-CHDD) is proposed for an efficient multi-view face recognition, and its theoretical convergence is also analyzed. Extensive experimental results on real face image datasets indicate the effectiveness of the proposed multi-view method. Show more
Keywords: Multi-view face recognition, unavoidable phenomenon, common hidden space, multi-view support vector machine
DOI: 10.3233/JIFS-181048
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5245-5259, 2019
Authors: Ghomi-Avili, Morteza | Khosrojerdi, Amir | Tavakkoli-Moghaddam, Reza
Article Type: Research Article
Abstract: This paper presents a multi-objective model for the closed-loop supply chain network design (CLSCND) with a price-dependent demand while considering random disruptions and shortage. This network consists of suppliers, production centers, collection/inspection centers, disposal centers, and market zones. In this model, a demand function is assumed to be a function of price offered to the customer by two different linear and exponential forms. Different resilience strategies including lateral transshipment among production centers and multi-source allocation are applied to model the resilient supply chain network design problem. Moreover, the importance of time for costumers is led to consider different transportation methods …for fulfilling the customers’ demand. Then, three different objective functions were incorporated when shortage is allowed and the unfulfilled demand will be back ordered. Then, a compromise programming method is used to convert the multi-objective model to a single-objective equivalent form. Furthermore, the application of the model is examined in a real industrial case involved in the production and distribution of glass. Finally, and the numerical results arrive at helpful managerial insights. Show more
Keywords: Closed-loop supply chain, disruption, shortage, compromise programming, uncertainty
DOI: 10.3233/JIFS-181051
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5261-5272, 2019
Authors: Samadi, Aliasghar | Jazaeri, Mostafa
Article Type: Research Article
Abstract: An isolated network with Wind Turbine implemented by Double Fed Induction Generator (WTDFIG) that maintaining different electrical variables in safe ranges following a severe transient condition is always a serious challenge. This paper proposes a control scheme based on Auto-Tuning Fuzzy PI (ATFPI) concept for the Rotor Side Converter (RSC) of the DFIG by online tuning of the output scaling factor of the ATFPI for enhancement the transient behavior of the system under various condition of operation. The scheme includes a coordinator unit which is elaborated to effectively regulate the frequency and active power of the system. The performance of …the proposed ATFPI controller is evaluated in a typical network in Matlab Simulink environment. Obtained results show that the control can successfully meet all functions drawn in the scope and easily put behind the conventional competitors like conventional PI and/or fuzzy PI controllers. Show more
Keywords: DFIG, Auto Tuning Fuzzy PI(ATFPI) controller, transient condition, isolated system, coordinator unit
DOI: 10.3233/JIFS-18106
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5273-5289, 2019
Authors: Nannan, Zhang | Chao, Luo
Article Type: Research Article
Abstract: This paper proposes a fuzzy cognitive map scheme for real-time online data prediction. The fuzzy cognitive maps (FCMs) are constructed on the basis of abstracting a numerical time series into a limited number of nodes (concepts), and used as a modeling tool for predicting time series. By representing time series in terms of information granules constructed in the space of amplitude and change of amplitude of the time series, a fuzzy cognitive map is dynamically constructed by using the set of information granule, where the particle swarm optimization (PSO) is utilized to study the parameters. In order to find better …weights in the global search process, each parameter of the particle swarm algorithm (PSO) is not set to a fixed value but adaptively changes. In this paper, a dynamic fuzzy C-means clustering algorithm is used to online adjust the cluster center and weight according to the impact of the incoming data at the current moment such that the model can capture real-time changes in the data information. The proposed approach is illustrated in detail by a series of experiments using a collection of publicly available data. Show more
Keywords: Fuzzy cognitive maps, information granules, particle swarm optimization (PSO), dynamic fuzzy C-means
DOI: 10.3233/JIFS-181064
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5291-5303, 2019
Authors: Zeng, Jiasheng | He, Jiali | Chen, Rongping
Article Type: Research Article
Abstract: An information system as a database that shows relationships between objects and attributes is a crucial mathematical model in the field of artificial intelligence. A real-valued information system is an information system where information function values of each attribute are real numbers. This paper explores information structures in an incomplete real-valued information system. Distances between two objects in a given subsystem of an incomplete real-valued information system is first constructed. Then, the fuzzy T cos -equivalence relation, induced by this subsystem by using Gaussian kernel method, is obtained, where Gaussian kernel is based on this distance. Next, information structure …of this subsystem is proposed. Moreover, relationships between two information structures are studied from the two aspects of dependence and separation. Finally, the dependence between two information structures is studied by using inclusion degree. These results will be helpful for establishing a framework of granular computing. Show more
Keywords: Granular computing, Incomplete real-valued information system, Gaussian kernel, Information granule, Information structure, Dependence; Inclusion degree, Information structures
DOI: 10.3233/JIFS-181097
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5305-5318, 2019
Authors: Chen, Neiping | He, Jiali
Article Type: Research Article
Abstract: A set-valued information system is the generalization of a single-valued information system and its information structures reflect the internal features of this kind of information system. This paper investigates information structures in a set-valued information system from granular computing viewpoint, i.e., information structures are viewed as granular structures. The distance between two objects in a set-valued information system is first introduced. Then, the fuzzy T cos -equivalence relation, induced by this kind of information system by using Gaussian kernel method, is obtained, where Gaussian kernel is based on this distance. Next, information structures of this kind of information system …are described by set vectors. Moreover, relationships between information structures are studied from two sides of dependence and separation. Finally, as a simple application for the proposed information structures, granularity measure of uncertainty for a set-valued information system is investigated. These results will be helpful for establishing a framework of granular computing in an information system. Show more
Keywords: Set-valued information system, granular computing, distance, information granule, information structure, dependence, information distance, inclusion degree, entropy
DOI: 10.3233/JIFS-181098
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5319-5331, 2019
Authors: Zhao, Feng | Li, Chaoqi | Liu, Hanqiang | Fan, Jiulun
Article Type: Research Article
Abstract: Interval valued fuzzy c-means (IVFCM) clustering algorithm is one of effective clustering algorithms. When applied to image segmentation, IVFCM includes three problems as follows: (1) It is sensitive to the initial values of algorithm and may easily fall into the local optimal. (2) The algorithm is sensitive to the image noise and cannot obtain the satisfying performance on images corrupted by noise. (3) It always performs image segmentation under one objective function, therefore it cannot meet multiple practical needs. In order to address these problems, a multi-objective interval valued fuzzy clustering algorithm is proposed in this paper. This method constructs …two novel interval valued fuzzy fitness functions which utilize the non-local spatial information of the image. Then a new mutation operator combining the interval valued fuzzy information of image is designed. Furthermore, an effective interval valued fuzzy cluster validity index using the non-local spatial information of image is presented to select a single solution from the non-dominated solution set. Experimental results show that the proposed method behaves well in noisy image segmentation. Show more
Keywords: Image segmentation, multi-objective optimization, interval valued fuzzy clustering, non-local spatial information
DOI: 10.3233/JIFS-181191
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5333-5344, 2019
Authors: Rehman, Noor | Ali, Abbas | Ali Shah, Syed Inayat | Irfan Ali, Muhammad | Park, Choonkil
Article Type: Research Article
Abstract: The extension of rough set model is a crucial and vast research direction in rough set theory. Meanwhile decision making can be considered as a mental process in which human beings make a choice among several alternatives. However, with the increasing complexity of real decision making problems, the decision makers frequently face the challenge of characterizing their preferences in an uncertain context. In the present paper, we initiate a multi attribute group decision making problem in the presence of multi attribute and multi decision in decision making with preferences. We further present the concept of soft preference relation and soft …dominance relation corresponding to decision attribute in the multi criteria and multi decision information system. Further we present the idea of variable precision multi decision soft dominance based rough set model and their applications in solving a multi agent conflict analysis decision problem. The proposed method addresses the limitations of the Pawlak’s model and Sun’s conflict analysis model and thus improve these models. Finally, the results on labor management negotiation problems show that the proposed algorithms are more effective and efficient for feasible consensus strategy when compared with other techniques. Show more
Keywords: Rough set, soft set, preference relation, inclusion degree, soft preference relation
DOI: 10.3233/JIFS-191197
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5345-5360, 2019
Authors: Kim, Hee Sik | Neggers, Joseph | Ahn, Sun Shin
Article Type: Research Article
Abstract: In this paper, we introduce the notions of an almost φ -fuzzy subalgebra and an almost φ -fuzzy semi-ideal in groupoids by using the concept of a function. This concepts are generalizations of a fuzzy subalgebra and a fuzzy ideal in groupoids respectively. We discuss some relations between almost φ -fuzzy subalgebras and vanishing, level subsets. By introducing the notions of (μ , φ )-extremes, e -ideals, we obtain several properties of almost φ -fuzzy subalgebras. The relations between almost φ -fuzzy semi-ideals and (μ , φ )-special elements are discussed. Finally we discuss fuzzy algebraic structures of almost …φ -fuzzy semi-ideals by diagrams. Show more
Keywords: almost φ-fuzzy subalgebra (semi-ideal), BCK/BCI-algebra, (weakly) vanishing, (pre-) level subset, (weak) fuzzy subalgebra property, (μ, φ)-(extreme, special), e-ideal, Bin (X)
DOI: 10.3233/JIFS-181220
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5361-5368, 2019
Authors: Zhang, Yulong | Zhou, Yisu | Duan, Menglan | Duan, Lixiang | Zhang, Xin | Jiang, Liuyi
Article Type: Research Article
Abstract: This paper proposes a novel symbolic representation method of feature extraction for fault diagnosis and condition monitoring. The Symbolic Aggregate approXimation (SAX) technique basically transforming real-valued time series into symbol sequences, has been proven as a newly developed tool of feature extraction for fault diagnosis. However, the original SAX is based on the Piecewise Aggregate Approximation (PAA) representation, which is primarily transformed by the calculation of mean value of the equal sized data subsection for dimensionality reduction. Such mean value-based method has a high possibility of missing important information patterns in vibration signals. To overcome this limitation, an enhanced SAX …(ESAX) is proposed to extract fault features well from vibration signals. The ESAX utilizes mean value together with two additional important points (the max and min points) to conduct the symbol representation in PAA process. Next, the Shannon entropy technique is conducted on the symbol sequences generated by ESAX to extract features for classification tasks. Compared with SAX, the ESAX can extract more comprehensive signal characteristics considering important information points and local fault patterns. The effectiveness and superiority of the ESAX were validated by experimental studies using the fault signals of rolling bearings. Show more
Keywords: Symbolic aggregate approximation (SAX), enhanced SAX, bearing defect diagnosis, fault pattern
DOI: 10.3233/JIFS-181246
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5369-5381, 2019
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