关键词: 软件可靠性增长模型，动态模糊神经网络，遗传算法，短期预测

Abstract: The parameters of dynamic fuzzy neural network were dynamically adjusted by genetic algorithm(GA- DFNN)，and GA-DFNN was used to study software reliability growth model(SGRM). The optimal solution of DFNN' s parameters was resolved by genetic algorithm in the DFNN's training process, and according to the DFNN which has the optimal parameters, software failure data prediction model was established. According to 3 groups of software de- fects data, we compared the SGRM's predictive ability established by GA-DFNN with SGRM's predictive ability estab- lished by fuzzy neural network(FNN) and I3P neural network(BPN). The simulation results confirm that the SRGM es- tablished by GA-DFNN has steady short period prediction, and its short period prediction error is small and it has some versatility.

Key words: Software reliability growth model,Dynamic fuzzy neural network,Genetic algorithm,Short period prediction