Algorithm based on fuzzy neural network for power grid fire warning
Aiming at the problems of low prediction accuracy and weak anti-interference ability of power grid fire early warning system based on threshold discrimination method,a power grid fire early warning algorithm based on fuzzy neural network was proposed.The neural networks were used to learn large-scale power grid data,fuzzy logic reasoning algorithms were used to improve the reasoning ability of predicted results,and neural network learning capabilities for large-scale data and reasoning capabilities of fuzzy logic algorithm were combined to analyze power grid line parameters for the improvement of the accuracy and anti-interference ability of power grid fire early warning system.Experiments and simulation results show that the as-proposed method can significantly improve the accuracy of power grid fire warning,and the use of fuzzy logic reasoning can obtain power grid fire warning results in close consistence with the actual situation.
power grid warninganti-interferenceneural networkfuzzy reasoningsignal processing
万方数据
维普
