Cloud model based on wavelet neural networks
Jian Xiao · Control theory & applications · 2011
A cloud model is an uncertain inference system based on linguistic rules.The number of linguistic rules is usually increased to improve the accuracy of identification.The high-dimension of the input space will cause the curse of dimensionality.To solve this problem a wavelet network cloud model(WNCM) is proposed.A wavelet neural network is used to substitute the consequent part of the cloud model.The structure and learning algorithm of WNCM are designed.Simulation results and comparison with other methods indicate that WNCM can approximate arbitrary nonlinear functions.The accuracy of identification is realized without increasing linguistic rules.