Research On Shanghai Real Estate Market Risk Early Warning Based On Artificial Neural Network

The rise and fall of the real estate industry not only affects the living standards of residents,but also reflects the current political and economic conditions of the country.At present,the rapid development of China's real estate market is also accompanied by problems such as random development and speculation.These problems are closely related to the lack of early warning research.Based on this,this article hopes to build an effective real estate early warning system to reduce the probability of undesirable phenomena in the real estate industry and promote the orderly development of the real estate industry.On the basis of careful study of the domestic and foreign research in the field of real estate early warning,this paper systematically sorts out the cycle and early warning theory of the real estate industry,and finally adopts the BP neural network to construct the early warning system.And take the first-tier city Shanghai as an example to make an empirical study.To this end,a total of 44 samples from the first quarter of 2009 to the fourth quarter of 2019 in Shanghai were collected in this study,and Matlab9.7 was used to provide them to the neural network for training to construct a real estate early warning model.The test sample test results prove that the generalization ability of this model is relatively good and can be used for early warning.Therefore,this article uses this model to warn the development of theShanghai real estate market in the second quarter of 2020,and finds that the development of the Shanghai real estate market in the second quarter of 2020 is "normal".