Risk Evaluation Of Real Estate Investment Based On The PSO Projection Pursuit Model

Real estate is a high return, high risk industry. The investment cycle is long, poor mobility, and multi-factors are characterized by investment income. But the investment risk is a neglected aspect. So, to choose a stable, continuous, and low risk investment project, will become the real estate investment assuring conditions. How to make effectively investment decision is an urgent problem to be solved.Projection pursuit is a method of high dimensional data processing and analysis, which can make exploratory analysis, and can make the deterministc analysis. However, the optimal projection index function is a complex nonlinear optimization problem, with the traditional method to deal with difficultly. So using particle swarm algorithm to solve this problem is more simple and effective.Firstly, according to the investigation and collection of materials, this dissertation summarized the influence of real estate investment risk evaluation index; then it used the projection pursuit to real estate investment risk assessment indexes normalized processing and established the real estate investment risk evaluation model of the projection pursuit; meanwhile, the particle swarm optimization algorithm was used to search the optimal projection direction, and greatly improved the computational efficiency and stability; finally, this dissertation established the projection pursuit based on PSO with high dimensional data model to solve the characteristics of real estate investment risk evaluation of the scheme, and chose the best solution for policymakers provides scientific basis.