Adaptive Genetic Algorithm For Multi Layer RBF Network

This article presents a kind of algorithm that is using adaptive genetic algorithm based onfloating point coding to train the center and width of t multi-layer radial basis functionnetwork.Through computer simulation of the unit and multivariate function approximation,itshows that the precision by this algorithm is much more higher than the precision by clusteringalgorithm for multi-layer RBF networks.On this basis,we apply the multi-layer radial basis function network based on adaptivegenetic algorithm of floating point coding to the prediction of Logistic and Mackey Glass chaotictime series.Compared with clustering algorithm for multi-layer RBF networks,the result shows thepredictive step is greatly improved.Finally, the paper put the multi-layer radial basis function network based on adaptive geneticalgorithm of floating point coding into numerical solutions of boundary value problems on thepartial differential equation in mathematical finance. Through computer simulation,the resultshows that it can use the algorithm to solve the numerical solutions of boundary value problemson the partial differential equation and the accuracy is very high.