Research Of Early Warning System In China Real Estate Market Based On Artificial Neural Network

With the advancement of the housing system reform and urbanization, Real estate industry is developing rapidly in our country, and its influence to national economy of our country is becoming deeper and deeper. The booming of the real estate industry has played an important role in improving our residents’living and stimulating economic growth. However, the rapid growth of real estate investment brings a series of problems. Recent years, the price of property rising rapidly, market risk increases gradually. More and more arguments about the real estate bubble appears. So, establishing an early warning system to monitor the real estate market has important significance to the development of our county’s real estate industry.Real estate early warning is part of economy early warning. This article firstly summarized the research of economy early warning home and abroad, and then analyzed the research status of real estate early warning in our country and its problems. Through the comparison on the advantages and disadvantages of the existing early warning method, this article decided to build the real early warning system based on artificial neural network, for its lots of features such as nonlinearity, fault tolerance, easy to operate, etc. On the basis of a lot of reading to relevant literature, this article established its early warning systems. The indexes are selected from the real estate industry development speed, the real estate industry interior balance and the real estate industry and the urban economy coordination three sides. All the indexes are those mostly be used and typical ones. The idea of building the early warning system based on artificial neural network is as follows:first, choose the warning indicator to appraise the warnings situation of the past years. Then, choose the alarm indicator. Finally, a program realizing the training of artificial neural network is compiled in the thesis by the neural network box of Matlab7.0, and the early warning model of real estate market is built by training the samples.In order to have a comprehensive understanding of the real estate situation, the article chose Beijing, Chongqing and Weihai respectively as the typical of our country’s First-tier Cities, Second-tier Cities and Third-tier Cities to do our empirical research. By collecting related data, we get the training samples of the three cities for our artificial neural network and tested its accuracy. Then the article analyzes the real estate market of the three cites by the early warning model based on the artificial neural network, output of the model indicate that Beijing and Weihai real estate market of2013will on the degree of "hot", Chongqing real estate market of2013will on the degree of "normal".In view of the conclusion, the article simply analyzed the main reasons caused this consequence finally and come up with some solutions such as standardize the land management system, adjust the supply of city land, control the size of loan for real estate, adjust the housing supply structure, limit speculation in the property market, Increase the information transparency of the real estate market.Because the early warning research of real estate in our country is not mature, most early warning methods are only theoretical and can’t be used in practice. In spite of its superiority and scientificity of early warning system based on artificial neural network, there are many limitations in use for lack of data and a convincing indicator system for early warning. So the next research can strengthen in these aspects.