Abstract：In this paper, an improvement of GA is discussed, which uses the floating point representation, elitist model, arithmetic crossover, and non-uniform mutation. The problem of the fitting of pump’s cavitation test data is analysed, and solve it based on the modified GA. In the end, there is a case, compared with the traditional fitting way and the modified GA, to show the method validity.
唐平；李金伴；张荣标. 基于遗传算法的泵汽蚀试验数据拟合[J]. 排灌机械工程学报, 2002, 20(1): 37-39.
TANG Ping, LI Jin-ban, ZHANG Rong-biao. The Fitting of Pump’s Cavitation Test Data Based on Genetic Algorithms. Journal of Drainage and Irrigation Machinery Engin, 2002, 20(1): 37-39.
