Network-based Type-2 Fuzzy System with Water Flow Like Algorithm for System Identification and Signal Processing
| Autor: | Che-Ting Kuo, Ching-Hung Lee |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Fluid Flow and Transfer Processes
0209 industrial biotechnology Interval type-2 fuzzy inference systems Computer Networks and Communications General Engineering lcsh:A 02 engineering and technology Neural network Computational Mathematics 020901 industrial engineering & automation Chemistry (miscellaneous) Modeling and Simulation Water flow like algorithm 0202 electrical engineering electronic engineering information engineering Blind source separation 020201 artificial intelligence & image processing lcsh:General Works System identification Energy (miscellaneous) |
| Zdroj: | Smart Science, Vol 3, Iss 1, Pp 21-34 (2015) |
| ISSN: | 2308-0477 |
| DOI: | 10.1080/23080477.2015.11665633 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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