Study on Risk Estimation Based on the BAM-Hamming Neural Network

Modern ammunition system is a complicated system involving multiple disciplines. During its development, the presence of voice uncertain factors, brings many risks to the development work. In this paper the importance of risk analysis to the ammunition system development is elaborated and various methods of risk analysis and risk estimation are studied. The risk characteristic factors in the project development and their estimation method are given, and then the characteristic factors are transformed into the corresponding binary code serials. During the establishment of the risk estimation model, the BAM Hamming neural network is used, and the optimum encoding method is adopted, thus the error tolerance of the neural network is improved. With anti helicopter intelligent mine as an example, the efficiency and reliability as well as the practical value of the method are verified.