Pattern recognition with neural networks combined by genetic algorithm

Soft computing techniques have been recently exploited as a promising tool for achieving high performance in pattem recognition. This paper presents a hybrid method which combines neural network classifiers by genetic algorithm. Genetic algorithm gives us an effective vehicle to determine the optimal weight parameters that are multiplied by the network outputs as coefficients. The experimental results with the recognition problem of totally unconstrained handwritten numerals show that the genetic algorithm produces better results than the conventional methods such as averaging and Borda count.