The Structure of Boundary Decision Using the Back Propagation Algorithms

역전파 알고리즘을 이용한 경계결정의 구성에 관한 연구

The Back propagation algorithm is a very effective supervised training method for multi-layer feed forward neural networks. This paper studies the decision boundary formation based on the Back propagation algorithm. The discriminating powers of several neural network topology are also investigated against five manually created data sets. It is found that neural networks with multiple hidden layer perform better than single hidden layer.