Partition Fuzzy Domain With Multi-Gnanularity Representation of Data Basing on Hedge Algebra Approach

Anh, Nguyễn Tuấn; Son, Tran Thai

doi:10.15625/1813-9663/34/1/10797

Cited by 1 publication

(1 citation statement)

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“…Hedge Algebras (HAs) [7][8][9] introduced by Cat Ho and Wechler [7] have rigorous efficient applications in a lot of different fields such as fuzzy control [10], data mining [11][12][13][14], image processing [15], time tabling [16], etc. HAs provide a mathematical formalism to link fuzzy sets based computational semantics of linguistic terms with their inherent qualitative semantics, in which the semantics of linguistic terms is interpreted as the order-based semantics.…”

Section: Introductionmentioning

confidence: 99%

A Co-optimization PSO for Fuzzy Rule-Based Classifier Design Problem Based on Enlarged Hedge Algebras

Nguyen

Pham

2021

Period. Polytech. Elec. Eng. Comp. Sci.

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Fuzzy Rule-Based Classifier (FRBC) design problem has been widely studied due to many practical applications. Hedge Algebras based Classifier Design Methods (HACDMs) are the outstanding and effective approaches because these approaches based on a mathematical formal formalism allowing the fuzzy sets based computational semantics generated from their inherent qualitative semantics of linguistic terms. HACDMs include two phase optimization process. The first phase is to optimize the semantic parameter values by applying an optimization algorithm. Then, in the second phase, the optimal fuzzy rule based system for FRBC is extracted based on the optimal semantic parameter values provided by the first phase. The performance of FRBC design methods depends on the quality of the applied optimization algorithms. This paper presents our proposed co-optimization Particle Swarm Optimization (PSO) algorithm for designing FRBC with trapezoidal fuzzy sets based computational semantics generated by Enlarged Hedge Algebras (EHAs). The results of experiments executed over 23 real world datasets have shown that Enlarged Hedge Algebras based classifier with our proposed co-optimization PSO algorithm outperforms the existing classifiers which are designed based on Enlarged Hedge Algebras methodology with two phase optimization process and the existing fuzzy set theory based classifiers.

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