A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems

Kai, Meng Tay and Tze, Ling Jee and Lie, Meng Pang and Chee, Peng Lim (2013) A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems. In: 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013;, 7 July 2013 through 10 July 2013;, Hyderabad; India.

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Official URL: http://ieeexplore.ieee.org/document/6622522/

Abstract

In this paper, a new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems (FISs) is proposed. The framework encompasses an optimization-based Similarity Reasoning (SR) scheme and a new monotone fuzzy rule relabeling technique. A complete and monotonically-ordered fuzzy rule base is necessary to maintain the monotonicity property of an FIS model. The proposed framework attempts to allow a monotonicity-preserving FIS model to be constructed when the fuzzy rules are incomplete and not monotonically-ordered. An online feature is introduced to allow the FIS model to be updated from time to time. We further investigate three useful measures, i.e., the belief, plausibility, and evidential mass measures, which are inspired from the Dempster-Shafer theory of evidence, to analyze the proposed framework and to give an insight for the inferred outcomes from the FIS model

Item Type: Proceeding (Paper)
Uncontrolled Keywords: unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak, Belief; Evidential mass; Fuzzy inference system; Fuzzy rule relabeling; Monotonicity; Online updating; Optimization-based similarity reasoning; Plausibility
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Computer software
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: Saman
Date Deposited: 05 Apr 2017 07:22
Last Modified: 02 May 2017 02:47
URI: http://ir.unimas.my/id/eprint/15837

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