Information System Fault Diagnosis Based on SSA-BPNN
In order to improve the accuracy of information system fault diagnosis,avoiding BP neural network fall into local op-timization and improve the rate of convergence,an information fault diagnosis model based on BP neural network improved by sparrow search algorithm is proposed.Sparrow search algorithm is applied to optimize the initial weights and thresholds of BP neural network.Compared with PSO-BPNN and GA-BPNN,SSA-BPNN has better optimization ability and fault diagnosis pre-cision,providing a new method for fault diagnosis of information system.
万方数据
维普
