Research on Risk Recognition of Real Estate Projects Based on MIV-BP Neural Network Test
Xiaoli Li · Yunchou yu guanli · 2013
Real estate is a business of high risk.This paper establishes an optimized MIV-BP neural network(Mean Impact Value Back-Propagation Network)which is based on a successful Back-Propagation neural network to identify the risk of real estate projects and to analyze the influence of various factors in the risk of real estate projects,thus to provide some references about the risk recognition for the real estate projects investment decisions and to help the real estate companies to avoid the risk effectively.Some present data related real estate projects are adopted to test the accuracy and objectivity of this model.The test results show the MIV-BP neural network model has an excellent compatibility and more accuracy when it is used in the risk recognition of real estate projects which can meet the experts' evaluation requirements and has a good application value in the analysis of risk factors in real estate projects.