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Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems

In this paper, two issues relating to modeling of a monotonicity-preserving Fuzzy Inference System (FIS) are examined. The first is on designing or tuning of Gaussian Membership Functions (MFs) for a monotonic FIS. Designing Gaussian MFs for an FIS is difficult because of its spreading and curvature...

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Main Authors: Kai, Meng Tay, Chee, Peng Lim
Format: E-Article
Language:English
Published: IEEE 2011
Subjects:
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://ir.unimas.my/id/eprint/559/1/Optimization%20of%20Gaussian%20Fuzzy%20Membership%20Functions%20and%20Evaluation%20of%20the%20Monotonicity%20Property%20of%20Fuzzy%20Inference%20Systems.pdf
http://ir.unimas.my/id/eprint/559/
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spelling my.unimas.ir.5592015-03-23T08:08:59Z http://ir.unimas.my/id/eprint/559/ Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems Kai, Meng Tay Chee, Peng Lim T Technology (General) TK Electrical engineering. Electronics Nuclear engineering In this paper, two issues relating to modeling of a monotonicity-preserving Fuzzy Inference System (FIS) are examined. The first is on designing or tuning of Gaussian Membership Functions (MFs) for a monotonic FIS. Designing Gaussian MFs for an FIS is difficult because of its spreading and curvature characteristics. In this study, the sufficient conditions are exploited, and the procedure of designing Gaussian MFs is formulated as a constrained optimization problem. The second issue is on the testing procedure for a monotonic FIS. As such, a testing procedure for a monotonic FIS model is proposed. Applicability of the proposed approach is demonstrated with a real world industrial application, i.e., Failure Mode and Effect Analysis. The results obtained are analysis and discussed. The outcomes show that the proposed approach is useful in designing a monotonicity-preserving FIS model. IEEE 2011 E-Article NonPeerReviewed text en http://ir.unimas.my/id/eprint/559/1/Optimization%20of%20Gaussian%20Fuzzy%20Membership%20Functions%20and%20Evaluation%20of%20the%20Monotonicity%20Property%20of%20Fuzzy%20Inference%20Systems.pdf Kai, Meng Tay and Chee, Peng Lim (2011) Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems. IEEE.
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Kai, Meng Tay
Chee, Peng Lim
Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems
description In this paper, two issues relating to modeling of a monotonicity-preserving Fuzzy Inference System (FIS) are examined. The first is on designing or tuning of Gaussian Membership Functions (MFs) for a monotonic FIS. Designing Gaussian MFs for an FIS is difficult because of its spreading and curvature characteristics. In this study, the sufficient conditions are exploited, and the procedure of designing Gaussian MFs is formulated as a constrained optimization problem. The second issue is on the testing procedure for a monotonic FIS. As such, a testing procedure for a monotonic FIS model is proposed. Applicability of the proposed approach is demonstrated with a real world industrial application, i.e., Failure Mode and Effect Analysis. The results obtained are analysis and discussed. The outcomes show that the proposed approach is useful in designing a monotonicity-preserving FIS model.
format E-Article
author Kai, Meng Tay
Chee, Peng Lim
author_facet Kai, Meng Tay
Chee, Peng Lim
author_sort Kai, Meng Tay
title Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems
title_short Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems
title_full Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems
title_fullStr Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems
title_full_unstemmed Optimization of Gaussian Fuzzy Membership Functions and Evaluation of the Monotonicity Property of Fuzzy Inference Systems
title_sort optimization of gaussian fuzzy membership functions and evaluation of the monotonicity property of fuzzy inference systems
publisher IEEE
publishDate 2011
url http://ir.unimas.my/id/eprint/559/1/Optimization%20of%20Gaussian%20Fuzzy%20Membership%20Functions%20and%20Evaluation%20of%20the%20Monotonicity%20Property%20of%20Fuzzy%20Inference%20Systems.pdf
http://ir.unimas.my/id/eprint/559/
_version_ 1644508651973509120
score 13.244414

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