Research On The Real Estate Price Forecast Based On Artificial Neural Network

While present stage real estate industry fast development, related "real estate market whether superheat" the question more and more is paid attention to by everybody, but to real estate market whether has "the froth" the question always does not have the consistent view. This article mainly carries on the analysis through the Back Propagation Neural Network to the Wuxi 2001-2003 year commodity housing price data, thus judges each influence factor to the commodity housing price influence.Paper take artificial neural network as main research tool. First, according to our country's estate industry present situation, through the analysis commodity housing price formation, has analyzed the housing market supply-demand relation, and had pointed out in this foundation affects the housing price various factors: The inhabitant receives which, the inhabitants expend structure, population and family structure, urbanized level, government policy and so on; Next, has carried on the analysis and the research to the artificial neuron network theory and the method; Finally, the union artificial neuron circuit analysis and affects the housing price the factor, has established the commodity housing price forecast model, through the model examination, forecast actually the precision is high. Indicated through this article research that, extends the artificial neural networks applies has in the commodity housing price forecast certain feasibility, the reliability and the usability.