Method for predicting radio disturbance of electric transmission line by using improved BP (back propagation) neural network

Abstract

The invention relates to a method for predicting radio disturbance of an electric transmission line by using an improved BP (back propagation) neural network. The method comprises the following steps of acquiring and preprocessing data parameters; establishing a BP neural network predicting model of the data parameters; performing optimal training on the BP neural network by using a genetic algorithm and a simulated annealing algorithm; and predicting radio disturbance of the electric transmission line by using the network. The method is high in prediction precision, high in convergence and high in stability; the problem that the BP neural network is caught in a local minimum point is solved; and the method has a great guiding significance on prediction of radio disturbance of the electric transmission line and research on reduction of radio disturbance.

Description

Technical field:

[0001] The invention relates to a radio interference prediction method, more particularly to an improved BP neural network transmission line radio interference prediction method. Background technique:

[0002] With the increase of the voltage level of the transmission line, the radio interference generated by the transmission line has aroused widespread concern. Reducing the electromagnetic environment impact of transmission lines and reducing the radio interference around the line is the work that designers in various countries have been studying, and how to accurately predict the radio interference of the line is the premise of the research work. At present, transmission line radio interference is predicted based on the empirical formula method and excitation function method recommended by CISPR. However, the mechanism of radio interference is very complicated, affected by many factors such as voltage, current, wire cross section, wire layout, meteorologi...

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