A Fault Diagnosis Method of Power Transmission Networks Based on Decision Trees and Spiking Neuron P Systems

To deal with the uncertain and incomplete fault information, a fault diagnosis method of power transmission networks based on decision trees and fuzzy reasoning spiking neural P system is proposed. Firstly, the target network is divided into several small subnets by the weight network segmentation method, and then the original fault decision table is trained by a decision tree algorithm to reduce the fault information and extract the fault production rules for the target transmission network. Then, fault diagnosis models based on fuzzy reasoning spiking neural P systems are built to find faulty sections. Finally, case studies are carried out with the IEEE 14 bus test system. Experimental results show that the proposed method can diagnose faulty sections with high fault tolerance for the fault information.