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《Basic Automation》 2001-01
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A Class of Hybrid Strategy to Estimate Model Parameters

WANG Ling 1, LI Wen feng 1, ZHENG Da zhong 1,LI Qing sheng 2(1. Dept. of Automation, Tsinghua University, Beijing 100084,China; 2. Dept. of Physics, BUAA,Beijing 100083,China)  
Reasonably combining the parallel structure of genetic algorithm with the controllable jumping property of simulated annealing, a class of effective and general hybrid optimization strategy is proposed and applied to estimate the parameters of various kinds of models. Numerical simulation results on benchmarks demonstrate the effectiveness of the hybrid strategy.
【Fund】: 国家自然科学基金资助项目 !(696840 0 1) ;; 国家攀登计划项目! (970 2 110 17)
【CateGory Index】: TP15
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