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

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.

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: Fuzzy Inference System, monotonicity property, Gaussian membership functions, sufficient conditions, monotonicity testing, UNIMAS, University Malaysia Sarawak, ENgineering, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, IPTA, education
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: Karen Kornalius
Date Deposited: 16 Jan 2014 02:43
Last Modified: 23 Mar 2015 08:08
URI: http://ir.unimas.my/id/eprint/559

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