Use of immune self-adaptation wavelet for data mining

Abstract

Based on an existing artificial neural network, a learning algorithm of the immune self-adaptation wavelet neural network is proposed which integrates the immune mechanism and the structure of neural information processing. This model makes it easy for a user to directly utilize the characteristic information of a pending problem and to simplify the original structure through adjusting the activation function with prior knowledge. Theoretical analysis and a simulation test for a data mining problem show that this method is effective and feasible.