Author(s)

Xiaohan Song, Xiaojing Zhang, Jingru Chen

Corresponding Author

Xiaohan Song

ABSTRACT

With the rapid development of the real estate industry in recent years, the trend of housing prices has become faster and faster, and the factors affecting housing prices are complex. Therefore, studying the influencing factors of housing prices and predicting housing prices are of great significance to the development of the national economy. In this regard, this paper proposes a method that combines genetic algorithm and BP neural network, optimizes the weights and thresholds of BP neural network through genetic algorithm, and establishes a housing price prediction model based on genetic algorithm to optimize BP neural network. The simulation results show that the convergence speed and prediction accuracy of the BP neural network prediction model optimized by genetic algorithm have been greatly improved. With this method, it is possible to accurately predict the changes in housing prices in my country, which has very important reference value.

KEYWORDS

Genetic algorithm, BP neural network, housing price, prediction model,