Research On RS-ANN Based Financial Evaluation Model On Real Estate Industry

Along with the rapid development of our economy and the increasingly intensecompetition, the environment on which enterprises depend for existence is becomingmore complex. Because of the bad management, many real estate listed companiesrun into financial trouble, and even face financial crisis or the risk of bankruptcy.Therefore, it’s very important for the business operator to find the sign of financialcrisis based on the prediction from the existing financial database, so that effectivemeasures can be taken to improve his operation and prevent the emergence offinancial crisis. Artificial neural network, as a nonlinear modeling and forecastingmethod, has better quality of nonlinear and higher value of approximation andgeneralization ability. It attempts to classify and predict the complex data throughsimulating the method of information disposal and memory by brain neurons.Currently, this research has been widely used to predict and obtained good results.This paper uses the rough sets,neural network method and latest data toconstruct the financial crisis pre-warning model and test whether it works.This article analyzes the mechanism of the financial pre-warning and keyfinancial ratios, proposes the screening method of financial indicators based onnormal test, designs the specific method and inspection standard of pre-warningmodel, establishes pre-warning model on the basis of BP neural network. After that,this paper carries on a research on the data of listed companies by using Matlab.Empirical study’s result indicates that financial pre-warning method based on BPartificial neural networks is feasible. It provides a new valid method for financialpre-warning.