In this paper, the depth feature selection technology is proposed. According to the different characteristics of feature extraction methods, a multi-layer feature extraction structure is formed, and selection variables are introduced to construct a global optimization model that enhances the feature expression of data sets from horizontal to vertical, so as to realize the adaptive feature selection of the prediction model as a whole. The real-coded harmony search algorithm was combined with BP, RNN and RBF neural network to optimize model structure and parameter. Experiments show that compared...
