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

As the real estate industry has been the mainstay industry of national economy, it is important to ensure its health development. Scientific early warning system of real estate market is helpful to the healthy development of real estate industry as it can offer reference to the market players, including the macro-control of government. But the current research of early warning of real estate market can not reflect the complex relationship between warning indicators and degree of alarm and loss the veracity of warning. So this thesis introduces the neural network of high function fitting ability into early warning of real estate market, builds a real estate market early warning system based on the artificial neural network by reflecting the complex relation between warning indicators and degree of alarm, and will improve the accuracy of real estate market early warning.Against this background, the thesis gets the idea of building the early warning system based on artificial neural network into shape firstly started with the economy early warning theory and business fluctuation theory. Next, it makes the empirical analysis with a sample of Shenzhen. At the direction of my tutor, interview and questionnaire survey to the experts of institutions such as Shenzhen Municipal Bureau of Land Resources and Housing Management and China Vanke Co.,Ltd were done and the data from 1986 which is related to real estate was collected in Shenzhen. As a result, 17 samples are obtained from these data. On the next step, 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. Testing result indicates that the model built in the thesis is qualified for the early warning of real estate market. At last, the thesis analyzes the Shenzhen real estate market by the early warning model based on the artificial neural network, output of the model indicate that the Shenzhen real estate market of 2005 will on the degree of "normal".The main innovations of the thesis concentrate on two aspects: First of all, to the question of disorder in the concept of real estate early warning indicator, the thesis constructs the warning indicator system and alarm indicator system on the basis of the prosperity indicator system. Second, introduces the neural network into the real estate market early warning and builds a real estate market early warning system based on the artificial neural network and improves the accuracy of real estate market early warning.Being enslaved to research experience, capability and time, there are still some shortcomings in the thesis. Firstly, as the short history of domestic real estate market can not provide enough samples for the train of artificial neural network, capability of real estate market early warning system based on the artificial neural network will be restricted. Secondly, the absence of analyzing in single warning indicator will be not propitious for searching the origin of alarm and obviating the alarm of real estate market. So the next research can strengthen in these aspects.