Title :
Parameter Identifications In Differential Equations By Gene Expression Programming
Author :
Jiang, Dazhi ; Wu, Zhijian ; Kang, Lishan
Author_Institution :
Wuhan Univ., Wuhan
Abstract :
As for inverse problem, there exist lots of traditional mathematic and physical methods. In recent years, the burgeoning evolutionary algorithms have been widely utilized in many areas. Their global optimization, parallelism, and effectiveness are widely applied to functional optimization problems. A method based on gene expression programming is presented in this paper for identifying the parameter in inverse problems. The results show that the new method is very effective for solving the inverse problem even for the case with large noise in the observation data.
Keywords :
differential equations; genetic algorithms; inverse problems; parameter estimation; burgeoning evolutionary algorithms; differential equations; gene expression programming; inverse problem; parameter identifications; Computational modeling; Differential equations; Evolutionary computation; Gene expression; Genetic programming; Inverse problems; Optimization methods; Parallel processing; Parameter estimation; Software engineering;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.539