Solving variational and Cauchy problems with self-configuring genetic programming algorithm
Sergey Burakov, Eugene Stanislavovich Semenkin · International Journal of Innovative Computing and Applications · 2013
It is suggested to use genetic programming techniques for solving Cauchy problem and variational problem that allows getting the exact analytical solution if it does exist and an approximate analytical expression otherwise. Features of solving process with this approach are considered. Results of numerical experiments are given. The approach improvement is fulfilled by adopting the self-configuring genetic programming algorithm that does not require extra efforts for choosing its effective settings but demonstrates the competitive performance.