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Real Estate Investment Risk Gorecasting Model Based on PCA-BP Neural Network

ZHANG Ji-gang (Department of Mathematics,Xianning University,Xianning 437100,China)  
Real estate investment has some distinguishing features: heavy invest and long recovery etc.Its forming is influenced by various factors.Through principal component analysis,we have synthesized numerous indexes,eliminated information overlapping of s real estate investment risk system,using BP network altitudinal nonlinear map,we have efficiently predicted real estate investment risk.After having been compared with BP network model,the result proves that the method is of high precision and great applicability.
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