Application of Combined Neural Network Based on Entropy Method in Smart City Forecast Problem

Abstract

With the continuous development of the national big data strategy and the construction of Digital China, cities have been given new connotations and requirements. This paper takes the real estate price changes in Hainan Province as the background, collects relevant information and data, and makes relevant analysis and reasonable predictions for the housing price changes in Hainan Province. This paper comprehensively considers the prediction defects of MEA_BP neural network, Elman neural network and Wavelet neural network, and uses a combination algorithm based on entropy method to comprehensively consider the results of all prediction models. On the one hand, it can improve the prediction accuracy of the model, and on the other hand, it can reduce the sensitivity of the prediction results to changes in a certain factor, making the prediction results more reliable. This paper establishes a multiple and effective new era smart city prediction model, which provides a reference for building a new city database supported by a new generation of information technology.