THE EVOLUTIONARY MODELING ALGORITHM FOR SYSTEM OF ORDINARY DIFFERENTIAL EQUATIONS
Kang Li · Chinese Journal of Computers · 1999
Based on the properties of self adaptation, self organization and self learning of evolutionary algorithms, a hybrid evolutionary modeling algorithm is proposed in this paper to solve the modeling problem of ordinary differential equations (ODEs). Its main idea is to embed a genetic algorithm (GA) into genetic programming (GP) where GP is employed to optimize the structure of a model, while a GA is employed to optimize the parameters of the model. It has taken the first step to making the modeling process of ODEs done automatically as well as giving reliable predictions. The numerical experiments show that multiple highly precise ODEs models can be searched out in a reasonable time and within fewer generations, and their predicted values surprisingly coincide with the exact solutions of the known ODEs using this algorithm.