Icing Forecasting of Transmission Lines with a Modified Back Propagation Neural Network-Support Vector Machine-Extreme Learning Machine with Kernel (BPNN-SVM-KELM) Based on the Variance-Covariance Weight Determination Method

Icing Forecasting of Transmission Lines with a Modified Back Propagation Neural Network-Support Vector Machine-Extreme Learning Machine with Kernel (BPNN-SVM-KELM) Based on the Variance-Covariance Weight Determination Method

Stable and accurate forecasting of icing thickness is of great significance for the safe operation of the power grid. In order to improve the robustness and accuracy of such forecasting, this paper proposes an innovative combination forecasting model using a modified Back Propagation Neural Network-...

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Bibliographic Details
Main Authors: Dongxiao Niu, Yi Liang, Haichao Wang, Meng Wang, Wei-Chiang Hong
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Energies
Subjects:
icing forecasting
back propagation neural network
mind evolutionary computation
bat algorithm
support vector machine
extreme learning machine with kernel
variance-covariance
Online Access:https://www.mdpi.com/1996-1073/10/8/1196

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