The General Regression Neural Network Based on the Fruit Fly Optimization Algorithm and the Data Inconsistency Rate for Transmission Line Icing Prediction

The General Regression Neural Network Based on the Fruit Fly Optimization Algorithm and the Data Inconsistency Rate for Transmission Line Icing Prediction

Accurate and stable prediction of icing thickness on transmission lines is of great significance for ensuring the safe operation of the power grid. In order to improve the accuracy and stability of icing prediction, an innovative prediction model based on the generalized regression neural network (G...

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Bibliographic Details
Main Authors: Dongxiao Niu, Haichao Wang, Hanyu Chen, Yi Liang
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Energies
Subjects:
icing prediction
general regression neural network (GRNN)
fruit fly optimization algorithm (FOA)
data inconsistency rate (IR)
Online Access:https://www.mdpi.com/1996-1073/10/12/2066

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https://www.mdpi.com/1996-1073/10/12/2066

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