Research On Intelligent Forecast Method Of The Real Estate Price Index

The development of real estate has entered a new period,and of course the 2014 has been included. By investigating the development situation of the real estate market in 2014, the author find that there is a downward trend of the market. The defense sentiment index has fallen sharply, and the investment of the real property also grows slowly. To be noticed the sales grows negatively. At the same time, the price index influenced 70 cities. Obviously the real estate market is in a weak condition. Therefore the government has eased the restriction on purchasing as well as the limitation on the credit, and the result has revealed a warming condition currently.The real estate is the pillar in the economic. Undoubtedly the economic in China has shifted, and so does the real estate market. And the mature, ration and difference are the goals in a new age in the market. Across the country, the price is relatively higher and the price change is more difficult to control than other countries. As the barometer and thermometer of the real estate market, the price index should be studied and the law of it will provide reliable guidance for the government, investors and the home buyers. So it is necessary and meaningful to establish, distribute and implement the price index.Firstly, the real estate market is highly complex nonlinear system. Based on this, the thesis adds the chaos theory in the simulation experiment. By the theory, the experiment restored the function of a variety of factors and it is more objective. Secondly, the thesis introduce the Support vector machine(SVM) intelligent algorithm. The selection of optimal parameter by using the genetic algorithm, particle swarm optimization(PSO) algorithm, cross crossover method, then comparison to the results, finally the thesis establish a model combing the PSO-SVM. The idea of the rolling forecasts has been put forwarded. Then combining rolling forecasts and PSO-SVM further, through the rolling forecast, the results is more dynamic and intuitive. And the model can serve the government macroeconomic regulation and control, foreign investment and the consumer purchasing more accurately, timely and objectively. So the model has a certain practical value.