کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
497197 862878 2010 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatically extracting T–S fuzzy models using cooperative random learning particle swarm optimization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Automatically extracting T–S fuzzy models using cooperative random learning particle swarm optimization
چکیده انگلیسی

This paper proposes a methodology for automatically extracting T–S fuzzy models from data using particle swarm optimization (PSO). In the proposed method, the structures and parameters of the fuzzy models are encoded into a particle and evolve together so that the optimal structure and parameters can be achieved simultaneously. An improved version of the original PSO algorithm, the cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of PSO. CRPSO employs several sub-swarms to search the space and the useful information is exchanged among them during the iteration process. Simulation results indicate that CRPSO outperforms the standard PSO algorithm, genetic algorithm (GA) and differential evolution (DE) on the functions optimization and benchmark modeling problems. Moreover, the proposed CRPSO-based method can extract accurate T–S fuzzy model with appropriate number of rules.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 10, Issue 3, June 2010, Pages 938–944
نویسندگان
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