Power transmission line icing prediction method based on quantum particle swarm and wavelet nerve network

Abstract

The invention relates to a power transmission line icing prediction method based on a quantum particle swarm and a wavelet nerve network. The power transmission line icing prediction method based on the quantum particle swarm and a wavelet nerve network comprises the following steps of acquiring historical icing meteorological data, namely an ambient temperature, a humidity, a wind speed, a wind direction, an air pressure, a lead temperature and an icing thickness; establishing an icing thickness prediction model by means of the wavelet nerve network; performing initial parameter optimization on the model through adding a quantum particle swarm algorithm of interference factors; and inputting the historical icing data for obtaining a predicated power transmission line icing thickness. The power transmission line icing prediction method has advantages of high prediction precision, high convergence speed, etc. The power transmission line icing prediction method can effectively predicate a line icing change rule and can be applied for power transmission line icing disaster early warning and treatment.

Description

technical field [0001] The invention relates to the field of early warning of icing disasters on transmission lines, in particular to an icing prediction method for transmission lines based on quantum particle swarms and wavelet neural networks. Background technique [0002] In recent years, with the gradual construction of power infrastructure, the safety and reliability of transmission lines have received more and more attention. Since transmission lines are mostly exposed to the natural environment, their operation status is easily affected by various meteorological factors. In particular, icing on transmission lines in winter may affect the safety and stability of transmission lines, and even cause serious harm, resulting in huge economic losses. Therefore, it is of great practical significance to predict the thickness of icing on transmission lines and formulate effective anti-icing countermeasures to realize early warning and treatment of icing disasters. [0003] At...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a transmission line icing prediction method based on quantum particle swarms and wavelet neural networks. This transmission line icing prediction method based on quantum particle swarms and wavelet neural networks is used to solve the traditional BP neural network model. Problems such as non-unique prediction results, overfitting, easy to fall into local minimum, difficulty in determining initial parameters, etc.

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