Study On Risk Evaluation Of High-tech Projects Investment Based On Rough Sets And BP Neuron Network

High-tech is becoming a 21st century economic and social development the main driving force. Faced with this trend, an increasing number of enterprises pay more attention to high-tech than in the past, actively involved in the development of high-tech projects and investment. But the new high-tech projects to invest in risky, faces a variety of objective or subjective factors. Likely due to the risk caused by the incident extension of investment projects, suspension, failure or not the expected technical and economic indicators. Therefore, investment in the project before the investment risk assessment of the success or failure of high-tech investment has an extremely important role.Based on the analysis of the risk characteristics of high-tech projects on the basis of the actual conditions in China, and put forward a set of conditions for the high-tech investment projects and the establishment of indicators of risk assessment based on rough sets - BP neural network risk assessment model. Rough Set a powerful numerical analysis capabilities, and BP neural network is accurate approximation convergence capability, and it will be rough set of serial BP neural network, based on the establishment of a rough set - BP neural network investment in high-tech projects risk assessment model . Rough Set to the front as a model system to attribute reduction, and elimination of redundant sample, reducing BP neural network input dimension and the right to the hidden layer neurons of the number of connections, thereby raising the BP neural network training speed, speed and evaluation of the accuracy of purpose. Finally, the simulation results show that use of the hybrid model can achieve more satisfactory results.