Network-based Type-2 fuzzy system with water flow like algorithm for system identification and signal processing

Che Ting Kuo, Ching Hung Lee*

*Corresponding author for this work

研究成果: Article同行評審

10 引文 斯高帕斯(Scopus)

摘要

This paper introduces a network-based interval type-2 fuzzy inference system (NT2FIS) with a dynamic solution agent algorithm water flow like algorithm (WFA), for nonlinear system identification and blind source separation (BSS) problem. The NT2FIS consists of interval type-2 asymmetric fuzzy membership functions and TSK-type consequent parts to enhance the performance. The proposed scheme is optimized by a new heuristic learning algorithm, WFA, with dynamic solution agents. The proposed WFA is inspired by the natural behavior of water flow. Splitting, moving, merging, evaporation, and precipitation have all been introduced for optimization. Some modifications, including new moving strategies, such as the application of tabu searching and gradient-descent techniques, are proposed to enhance the performance of the WFA in training the NT2FIS systems. Simulation and comparison results for nonlinear system identification and blind signal separation are presented to illustrate the performance and effectiveness of the proposed approach.

原文English
頁(從 - 到)21-34
頁數14
期刊Smart Science
3
發行號1
DOIs
出版狀態Published - 2015

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