Surveying the methods of improving ANN generalization capability

The generalization capability of an artificial neural network (ANN) is the most important performance of it, but to obtain the good generalization capability of an ANN is not an easy thing. During about twenty years rapid development of ANN technology, many methods of improving the generalization capability have been proposed, but the generalization problem related to an ANN is still serious. This paper first narrates the existing methods of improving ANN generalization capability, sorting them in five categories. Second, the existing improving methods are evaluated and tested, their capabilities and shortcomings being pointed out. Finally, the concluding remarks are given and the prospective improving methods are discussed.