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《Computer Engineering and Design》 2007-16
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Research on heat conduction inverse problem based on quantum-behaved particle swarm optimization and particle swarm optimization

ZHANG Hong,XU Wen-bo,SUN Jun(Institute of Information Technology,Southern Yangtze University,Wuxi 214122,China)  
The research of heat conduction inverse problem starts late in domestic,there are lots of research methods,but ordinary methods are hard to be at the holistic best point.Purpose is to study the application of quantum-behaved particle swarm optimization(QPSO) in the two-dimensional heat conduction on the ground of classical particle swarm optimization(PSO) and how to use the above algorithm based on the objective function to seek the best parameter combination is introduced.In order to enhance the astringency and the stability of the algorithm,and the massive experiments are carried out.The results show in the solution heat conduction inverse problem optimization question,based on QPSO algorithm the performance is better than the classics PSO algorithm,and prove QPSO had determinate practical application value in the heat conduction domain.
【Fund】: 国家自然科学基金项目(60474030)
【CateGory Index】: TP301
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