Study On Investment Decision-Making Of Real Estate Based On Theory Of Projection Pursuit

With China's sustained and rapid development of the national economy as well as process of urbanization, real estate has become the engine of China's economic growth and pillar industries. The real estate investment decision-making is an important part of project development, which directly affects the degree of risk in project development, and the size of investment income. Real estate investment has the salient features of high risks and high uncertainty. Success or failure of the real estate investment decision-making on the enterprise's own survival and development will have a significant impact; therefore, it is necessary to improve the real estate enterprises to invest in scientific decision-making.Projection Pursuit theory is a king of new and extremely valuable high-tech, It is cross-discipline contain the statistics, applied mathematics and computer technology, it also belongs to the area of today's cutting-edge, which has been widely used in many fields and have made a valuable research results. This article will introduce Projection Pursuit principle into real estate investment decision-making process, the establishment of the corresponding projection pursuit classification model analysis and research is designed to provide a theoretical circles and the business community a viable real estate investment decision-making models and algorithms. Main tasks are as follows:(1) Systematically introduce the characteristics of real estate investment decision-making, main contents and common methods, which describes the types of risks and characteristics faced by decision-making process;(2) The projection pursuit cluster model is applied to the evaluation of the real estate investment decision-making, and use examples verify its rationality and superiority;(3) The pros and cons of each investment program will be reflected visually by the Projection value scatter plot;(4) Through a case study, compared with the other comprehensive evaluation method shows the superiority of this method.