A fault line selection method for small current grounding system
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摘要: 针对小电流接地系统故障选线方法难以适用于不同接地方式的问题,提出了一种基于粒子群优化RBF神经网络的小电流接地系统故障选线方法。该方法利用粒子群优化算法来优化RBF神经网络,将RBF神经网络要确定的参数作为粒子群优化算法的粒子。仿真结果表明,该方法收敛效率高、误差平方和小、选线准确率高、灵敏度高,具有一定的可行性。Abstract: In view of problem that fault line selection method for small current grounding system is difficult to be suitable for different grounding modes, the paper proposed a fault line selection method for small current grounding system based on RBF neural network optimized by particle swarm. The method uses particle swarm optimization algorithm to optimize RBF neural network, takes parameters confirmed by the RBF neural network as particles of the particle swarm optimization algorithm. The simulation result shows that the method has high convergence efficiency, small sum of square of error, high accuracy of line selection, high sensitivity and a certain feasibility.
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