標題: A Hybrid of Bacterial Foraging Optimization and Particle Swarm Optimization for Evolutionary Neural Fuzzy Classifier
作者: Chen, Cheng-Hung
Su, Miin-Tsair
Lin, Cheng-Jian
Lin, Chin-Teng
交大名義發表
電子工程學系及電子研究所
National Chiao Tung University
Department of Electronics Engineering and Institute of Electronics
關鍵字: Neural fuzzy classifier;bacterial foraging optimization;particle swarm optimization;classification;skin color detection
公開日期: 1-Sep-2014
摘要: This study presents a new evolutionary learning algorithm to optimize the parameters of the neural fuzzy classifier (NFC). This new evolutionary learning algorithm is based on a hybrid of bacterial foraging optimization and particle swarm optimization. It is thus called bacterial foraging particle swarm optimization (BFPSO). The proposed BFPSO method performs local search through the chemotactic movement operation of bacterial foraging whereas the global search over the entire search space is accomplished by a particle swarm operator. The NFC model uses functional link neural networks as the consequent part of the fuzzy rules. This study uses orthogonal polynomials and linearly independent functions in a functional expansion of the functional link neural networks. Finally, the proposed neural fuzzy classifier with bacterial foraging particle swarm optimization (NFC-BFPSO) is adopted in several classification applications. Experimental results have demonstrated that the proposed NFC-BFPSO method can outperform other methods.
URI: http://hdl.handle.net/11536/25184
ISSN: 1562-2479
期刊: INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
Volume: 16
Issue: 3
起始頁: 422
結束頁: 433
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