| Summary: | 碩士 === 國立中央大學 === 電機工程研究所 === 98 === In order to improve the performance of Particle Swarm Optimization (PSO) algorithm and to overcome the difficulty of selecting the appropriate acceleration coefficients, this thesis proposes an improved algorithm based on adaptive-fuzzy PSO algorithm [5], TIME-VARYING Particle Swarm Optimization, called TV-PSO. First, an adaptive-fuzzy PSO is adapted to generate the curves of the acceleration coefficients versus the differences between the consecutive values of two consecutive fitness functions. Then, each curve is simplified to three line segments to present the time-varying acceleration coefficients.
Finally, 14 classic functions with different complexities are utilized to test our proposed algorithm. As compared with the traditional PSO algorithm, Adaptive-fuzzy PSO Algorithm, PSO-TVAC and TA-PSO, it is found that the proposed time-varying coefficients are easy to be applied in the PSO algorithm and a better performance is obtained.
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