Research on Real Estate Sales Trend Prediction Based on Artificial Neural Network
Hainian Zhang, Qian Chen, Benyu Zhao · 2024
The sales price index of real estate is an effective tool to guide industry activities and market research, but the accuracy of prediction has always been paid more attention by people. With the continuous development of the real estate industry, the amount of data is getting larger and larger. Applying data mining technology to the real estate industry, processing and analyzing the sales data can truly reflect the value of the data. In this paper, taking the real estate data of a city in Jiangsu Province as an example, the quantitative research shows the modeling process. Based on ARMA model and the weighted least square method, the model is improved. Because the real estate market is a highly complex nonlinear system, the accurate description of the complex feature of house price trend is becoming more and more important. Artificial neural network is a new interdisciplinary subject. In recent years, it has been more and more applied to the prediction of practical problems, showing its broad application prospects. In particular, artificial neural network has great potential to predict the future behavior of nonlinear systems. BP neural network is applied to the real estate market monitoring and early warning system; This paper forecasts and monitors the change trend of the real estate market, and puts forward the corresponding early warning barriers of the real estate market, so as to provide a more scientific basis for the control of the urban real estate market.