DefinePK

DefinePK hosts the largest index of Pakistani journals, research articles, news headlines, and videos. It also offers chapter-level book search.

Efficient Cooperative Particle Swarm Optimization for TSK-Type Neural Fuzzy Systems and Its Classification Applications


Article Information

Title: Efficient Cooperative Particle Swarm Optimization for TSK-Type Neural Fuzzy Systems and Its Classification Applications

Authors: Cheng-Hung Chen

Journal: Journal of advances in applied & computational mathematics

HEC Recognition History
No recognition records found.

Year: 2015

Volume: 2

Issue: 1

Language: en

DOI: 10.15377/2409-5761.2014.02.01.6

Keywords: Particle Swarm Optimizationclassification.cooperative evolutionTSK-type neural fuzzy systems

Categories

Abstract

This study proposes a cooperative particle swarm optimization (CPSO) to optimize the parameters of the TSK-type neural fuzzy system (TNFS) for classification applications. The proposed CPSO uses cooperative behavior among multiple subswarms to decompose the neural fuzzy systems into rule-based subswarms, and each particle within each subswarm evolves by a specific particle swarm optimization (PSO) separately. Therefore, the CPSO can accelerate the search and increase global search capacity. Finally, the TNFS with CPSO (TNFS-CPSO) is adopted in several classification applications. Experimental results demonstrate that the proposed TNFS-CPSO method has a higher accuracy rate and a faster convergence rate than the other methods.


Paper summary is not available for this article yet.

Loading PDF...

Loading Statistics...