Optimizing Artificial Neural Networks through Layer Partition and Genetic Algorithms

抄録

Two methods of optimizing feed-forward Artificial Neural Networks (ANN) through Genetic Algorithm (GA) are presented. The connection weights of ANN are extracted out. The functions formulated having connection weights as variables are optimized through GA. The optimized connection weights replace the old ANN connection weights. The first method proposed gives closer results. The second method is a novel approach of ANN optimization through GA. This method produced exact values. The method is proved by designing spindle of cylindrical grinding machine.