To assess the complex system-s risk probability while the number of the simples was limited, the small probability assessment modeling method by small simples was put forward, and the mapped relationship between the cumulating probability and the extremum of the critical parameter was approached by nonlinear function. The risk probability assessment mathematic model was developed, and the basic assessment model was obtained by using nonlinear regress. The offered simples can not completely accorder with the assessment model, so the error was regarded as the object function, and the optimum probability assessment model was presented. In order to optimize the model-s distribution parameter, the improved genetic algorithm was adopted. The applied example of flight safety assessment was showed, and the flight risk probability was calculated by the limited simples. The precise is improved by the optimum approach function.
�˻���,������. ����ϵͳ��ȫ�Է����ĸ��ʷ�����������[J]. ϵͳ��������Ӽ���,1999,21(8):28-31 Gu Jifa, Zhao Liyan. Introduction of probabilistic risk assessment approach to analyze the safety of space systems[J]. Systems Engineering and Electronics, 1999,21(8):28-31(in Chinese)
������,�˻���. ���ʷ�������(PRA)�������ҹ�ĳ�ͺ����ػ����ȫ�Է����е�Ӧ��[J]. ϵͳ����������ʵ��,2000,20(6):91-97 Zhao Liyan, Gu Jifa. The application of probabilistic risk assessment approach to the safety analysis of one specific type of launch vehicle in China[J]. Systems Engineering-Theory and Practice, 2000, 20(6):91-97(in Chinese)
���ΰ�,�ⱦ��,������,��. ���С�����¼�Ԥ���ɹ��ʵ�һ��;��[J]. ����,2005,26(2):3-5 Pen Zhiban, Wu Baojun, Jiang Jianmin, et al. An improved exact forecast method for the little probability events[J]. Weather, 2005,26(2):3-5(in Chinese)
Davis L. Genetic algorithms and simulated annealing[M]. Los Altos:Morgan Kaufmann Publishers ,1987
Srinivas M, Patnaik L M. Adaptive probabilities of crossover and mutation in genetic algorithm[J].IEEE Trans Syst,Man,and Cybern.1994,24(4):656-667