Prediction model of insulator contamination degree based on adaptive mutation particle swarm optimisation and general regression neural network

Prediction model of insulator contamination degree based on adaptive mutation particle swarm optimisation and general regression neural network

The contaminants accumulated on the surface of transmission line insulator mainly come from the suspended particles in the air. Therefore, it is necessary to consider meteorological factors and environmental factors in the prediction of insulator contamination degree. In view of the advantages of ge...

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Bibliographic Details
Main Authors: Rumeng Wang, Ming Zhang, Yunpeng Jiang, Yong Yang
Format: Article
Language:English
Published: Wiley 2019-04-01
Series:The Journal of Engineering
Subjects:
particle swarm optimisation
insulator contamination
neural nets
power engineering computing
regression analysis
fault tolerance
environmental factors
PSO–GRNN models
transmission line insulator
suspended particles
meteorological factors
generalised regression neural network
equivalent salt deposit density
inertia weight
global optimal smoothing factor
ESDD
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8669

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https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8669

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