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-...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-08-01
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Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/10/8/1196 |