Software reliability growth model based on SAA-DFNN
Gai‐Ge Wang · Journal of Jilin University · 2012
Simulated Annealing Algorithm(SAA) is used to dynamically adjust the parameters of Dynamic Fuzzy Neural Network(SAA-DFNN).The SAA-DFNN is applied to study Software Reliability Growth Model(SRGM).The SAA is used to resolve the optimal solution of DFNN parameters in the DFNN software failure data training process.Then according to the obtained DFNN optimal parameters SAA sets up software failure data prediction model.Using three groups of software defect data,the predictive ability of the SRGM established by SAA-DFNN is compared with that of the SRGM established by Fuzzy Neural Network(FNN) and by BP Neural Network(BPN)and G-O model.Simulation results confirm that the SRGM established by SAA-DFNN has steady single-step ahead predictive ability with certain versatility and the prediction error is smaller.