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作者:

Pan, Guangyuan (Pan, Guangyuan.) | Qiao, Junfei (Qiao, Junfei.) (学者:乔俊飞) | Han, Honggui (Han, Honggui.) (学者:韩红桂)

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摘要:

Two drawbacks of Chaotic Particle Swarm Optimization (CPSO) are analyzed in the paper, the first one is the search in the initial state is helpless and the second is it is ineffective in jumping out of the local optimum at the later stage. An improved strategy of CPSO (HMCPSO) is introduced to modify these problems. This method uses the randomness, ergodicity and regularity of chaos to associates with PSO to improve the abilities of jumping out of local optimum and searching for the global optimum. Besides, the mechanism of judging the historical data of particles' location is proposed, by using which the excess operations of chaotic processes and the run time are reduced significantly. At the end, HMCPSO is applied in the optimization design of pipe network, the result shows the algorithm finds a lower cost point and the reliability is satisfactory. © 2013 TCCT, CAA.

关键词:

Particle swarm optimization (PSO) Optimization Control engineering

作者机构:

  • [ 1 ] [Pan, Guangyuan]College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Qiao, Junfei]College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Han, Honggui]College of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China

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ISSN: 1934-1768

年份: 2013

页码: 8022-8027

语种: 英文

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