Investment Risk Evaluation Model Research Based On Improved Genetic Neural Network

With the development of global economy, financial crisis has more and more influence on the risk investment. So, risk investment is full of risk every moment and it is also more impact on economic development. Therefore, evaluate investment risk scientific is become a necessary task between the process of investment risk. In order to reduce the risk of loss of investment, we are very necessary to take reasonable and effective method for a perfect evaluation system. Only in this way can we plotting coups at risk investment decisions, promote the development of high technology, and promote the national economy developing quickly and well. At present, there are some common evaluation decision models for risk investment. Such as risk evaluation techniques, AHP (Analytic Hierarchy technology Process) Hierarchy, portfolio risk assessment model, the linear programming model. These models provide effective tools and ideas for risk investment decision, but they have their limitations to some extent.Based on the previous research, a mathematical model is established by using dynamic artificial intelligence algorithm. At the same time, adding preferences factor come from investors, for fixing the result of evaluation in order to achieve the purpose of scientific decision. Firstly, this paper introduces the risk investment to the development of national economy, and then analyzes the significance of risk investment evaluation mechanism and characteristics, and risk assessment of the investment decision-making model and the existing methods applied limitations. At last, investment risk assessment system is structured through the experimental investigation with referring to the investment risk assessment standards. In this process, it give an important attention to the investment risk assessment methods, the improved genetic algorithm of neural network model to construct risk investment and the risk of superior performance about investment risk assessment and efficiency evaluation. Through in-depth research, this paper puts forward a kind of method that investors can undertake scientific decision according to the preference about "risk and benefit" under the influence of dynamic factors. Finally, it programs in the environment of R2009a MATLAB, and the investment risk model was tested and verified with example. Empirical study results show that the improved genetic algorithm of neural network can effectively improve the operation efficiency of the algorithm and the correctness of the risk evaluation system and rationality.