A New Mixed Algorithm Based on Feedforward Neural Networks

In this paper, a mixed algorithm based on feedforward neural networks is introduced. This algorithm combines rapidly descent method with conjugate gradient method to overcome shortcomings of the traditional back-propagation algorithm, such as slow convergence and possible running into local optimum being affected by poor initial weights and setup parameters. The result of simulations shows that the mixed algorithm can be used effectively.