Optimization of Support Vector Machine for Cable Fault Diagnosis Based on Salp Swarm Algorithm
In order to improve the accuracy of high-voltage cable fault diagnosis,a cable fault diagnosis method based on the optimization of SVM using the bottle sea sheath swarm algorithm is proposed.It uses cosine similarity to analyze the temporal characteristics of cable faults,the salp swarm algorithm to optimize the support vector ma-chine,and establishes a cable fault diagnosis model based on the salp swarm algorithm to optimize SVM.The dis-tribution network cable fault recording data is used for simulation analysis,and comparing it with other cable fault models.The results show that the diagnostic accuracy of SSA-SVM is 97.5%,which is higher than other models,The practicality and effectiveness of the cable fault diagnosis method proposed in this article have been verified.
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维普
