Abstract
According to such defects as that BP neural network is easy to fall into the local minimum values and is sensitive to the initial values of weights and thresholds, genetic algorithm was combined with BP neural network to improve the initial values of weights and thresholds. According to the fault diagnosis of complex system, based on cognitive science, its structure was decomposed; the fault diagnostic sub-model using genetic BP neural network was established to the different parts of the structure; D-S evidence theory was used to different sub-models for the global information fusion. GNN-DS diagnostic model was established for the fault diagnosis of complex system, this model reduced the uncertainty of fault diagnosis of complex system.
Published Version
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