Search

In this paper, an effective learning of neural network by using random fuzzy back- propagation (RFBP) learning algorithm is developed. Based on this new learning algorithm, neural network not only has an accurate learning capability, but also can increase the probability of escaping from the local minimum while neural network is training. For demonstrating the new algorithm we developed has its outperformance, the classifications of the non-convex in two dimensions (NC2) problem are simulated. For comparison, the same simulations by using conventional back-propagation (BP) learning algorithm with constant pairs of learning rate (α0.1-0.9) and momentum (ξ = 0.1-0.9) and stochastic BP learning are also performed. [ABSTRACT FROM AUTHOR]