Adaptive Weighted Fuzzy Particle Swarm Optimization and Its Application on the Design of the Spiral Inductor
碩士 === 國立中央大學 === 電機工程學系 === 104 === In this thesis, we propose a variant algorithm for Particle Swarm Optimization (PSO) which is called Adaptive Weighted Fuzzy Particle Swarm Optimization (AWFPSO). The algorithm combines two methods: AFPSO which uses fuzzy rules to adjust the acceleration par...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2016
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| Online Access: | http://ndltd.ncl.edu.tw/handle/11486484545244458334 |
| Summary: | 碩士 === 國立中央大學 === 電機工程學系 === 104 === In this thesis, we propose a variant algorithm for Particle Swarm Optimization (PSO) which is called Adaptive Weighted Fuzzy Particle Swarm Optimization (AWFPSO). The algorithm combines two methods: AFPSO which uses fuzzy rules to adjust the acceleration parameters of PSO, and FPSO which manipulates membership function values to obtain weights. We also take the second best particle into consideration to prevent the AWFPSO from falling into local optimum too earlier. The performance of AWFPSO is compared with several PSO algorithms in the literature by utilizing sixteen benchmark functions. Finally, we apply AWFPSO to optimizing the design of the spiral inductor of Radio Frequency Integrated Circuits (RFIC). From experimental results, the proposed method improves the performance of RFIC by enhancing the quality factor of the designed spiral inductor.
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