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《Journal of East China Jiaotong University》 2007-05
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Resolution Strategy for Ill-posed Inverse Problems Based on Multi-objective Optimization

MAO Li-jun(Civil Engineering Department of Nanjing University of Aerong Jiangshu Province 210016,China)  
The resolution strategy for ill-posed inverse problems encountered in science and engineering researches is put forward,based on multi-objective optimization.In the strategy,the residues of the equations of inverse problem corresponding with each measure are regarded as multi-objectives to be optimized,then the multi-objective is incorporated to one objective which can be optimized using genetic algorithm.Using the efficient information of each measure,the strategy gives a robust solution for the ill-pose inverse problem.Numerical examples show that the strategy's performances in solution precision and noise immunity are significantly better than least square method(LS) and Tikhonov regularization method when measurement noise lies in medium and low levels.
【Fund】: 国家自然基金项目(50508016/E080801)
【CateGory Index】: O224
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