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International Journal of Fuzzy Systems
IF
3.08
Papers
866
Papers 930
1 page of 93 pages (930 results)
Newest
#1Baoli Wang (Yuncheng University)
#2Jiye Liang (Shanxi University)H-Index: 38
Last.Jifang Pang (Shanxi University)
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Score functions play an important role in ranking hesitant fuzzy elements (HFEs) and hesitant fuzzy sets (HFSs). Currently, various kinds of HFE and HFS score functions have been investigated in the literature. However, the essential characteristic and generation mechanism of these score functions have not been systematically studied. To address these issues, this paper introduces an axiomatic definition of deviation degree measure and proposes a general form of dual HFE and HFS deviation score ...
The success of fuzzy clustering heavily relies on the proper feature space constructed by the input data. For nonspherical and overlapped clusters, kernel fuzzy clustering is more effective because it finds more proper feature space compared to conventional fuzzy clustering. Unfortunately, poor scalability of kernel fuzzy clustering is induced by the construction of a kernel matrix. To solve the problem, random feature-based method was presented to approximate the kernel function. More interesti...
#1Peide Liu (Shandong University of Finance and Economics)H-Index: 17
#2Baoying Zhu (Shandong University of Finance and Economics)
Last.Peng Wang (Shandong University of Finance and Economics)
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As we all know, the research and development (R&D) is crucial for enterprises. How to choose the R&D project is an important research topic, and at the same time, it is also a typical multi-attribute decision-making (MADM) problem. In this paper, we propose a novel MADM method for selecting the Yunnan Baiyao’s R&D project of toothpastes. Firstly, we use T-spherical fuzzy sets (T-SFSs) to express the evaluation information of the toothpastes from decision makers to overcome the shortcomings exist...
#1Guozheng Feng (Yantai University)
#2Mengying Ni (Yantai University)
Last.Jindong Xu (Yantai University)
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Remotely sensed imagery classification have a large amount of uncertainty related to the intraclass heterogeneity and the interclass ambiguity of objects. Fuzzy set theory can address the uncertainty effectively, while interval-valued model can improve the separability of samples. Therefore, we propose a novel interval-valued fuzzy c-means algorithm, which integrates the interval-valued model and preferential adaptive method. It preferentially adjusts the interval width according to MSE (mean-sq...
#1Tien-Loc Le (YZU: Yuan Ze University)H-Index: 3
#2Tuan-Tu Huynh (YZU: Yuan Ze University)H-Index: 2
Last.Fei Chao (Ha Tai: Xiamen University)H-Index: 10
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This paper proposes a new medical diagnosis algorithm that uses a K-means interval type-2 fuzzy neural network (KIT2FNN). This KIT2FNN classifier uses a K-means clustering algorithm as the pre-classifier and an interval type-2 fuzzy neural network as the main classifier. Initially, the training data are classified into k groups using the K-means clustering algorithm and these data groups are then used sequentially to train the structure of the k classifiers for the interval type-2 fuzzy neural n...
#1Shi-Yuan Han (Shandong Women's University)
#2Xiao-Fang Zhong (Shandong Women's University)
Last.Gong-You Tang (Ocean University of China)H-Index: 15
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This paper focuses on the fuzzy guaranteed cost \(H\infty\) control problem for uncertain nonlinear vehicle active suspension system with random actuator time delay. Its main contribution to the literature is that a fuzzy guaranteed cost \(H\infty\) controller (FGCHC) is proposed to ensure the resulting closed-loop vehicle active suspension system to be asymptotically stable and guarantee the performance index to be less than a preset upper bound. More specifically, taking the varying masses and...
#1Juan-juan Peng (Zhejiang University of Finance and Economics)H-Index: 2
#2Jian-qiang Wang (CSU: Central South University)H-Index: 13
Last.Xiao-hui Wu (CSU: Central South University)H-Index: 5
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Multi-hesitant fuzzy sets (MHFSs) are hesitant fuzzy sets (HFSs) with membership function, permitting the same evaluation value to be repeated several times. MHFSs can depict uncertain information more effectively than HFSs. This study defined three outranking relations of multi-hesitant fuzzy numbers (MHFNs), namely strong dominant, weak dominant and indifferent relationships, based on the elimination and choice translating reality (ELECTRE) I method. Thereafter, we discussed the corresponding ...
In this paper, the author proposes an innovative Chaotic Interval Type-2 Fuzzy Neuro-oscillatory Network (CIT2-FNON) for worldwide financial prediction. Inspired by the author’s original work on Lee-oscillator—a chaotic discrete-time neural oscillator with profound transient-chaotic property, CIT2-FNON provides: (1) effective modeling of Interval Type-2 Fuzzy Logic with Chaotic Transient-Fuzzy Membership Function (CTFMF); and (2) time-series recurrent neural network training and prediction with ...
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