publication . Article . 2017

Ice Cover Prediction of a Power Grid Transmission Line Based on Two-Stage Data Processing and Adaptive Support Vector Machine Optimized by Genetic Tabu Search

Xiaomin Xu; Dongxiao Niu; Lihui Zhang; Yongli Wang; Keke Wang;
Open Access
  • Published: 01 Nov 2017 Journal: Energies, volume 10, page 1,862 (eissn: 1996-1073, Copyright policy)
  • Publisher: MDPI AG
Abstract
With the increase in energy demand, extreme climates have gained increasing attention. Ice disasters on transmission lines can cause gap discharge and icing flashover electrical failures, which can lead to mechanical failure of the tower, conductor, and insulators, causing significant harm to people’s daily life and work. To address this challenge, an intelligent combinational model is proposed based on improved empirical mode decomposition and support vector machine for short-term forecasting of ice cover thickness. Firstly, in light of the characteristics of ice cover thickness data, fast independent component analysis (FICA) is implemented to smooth the abnor...
Subjects
free text keywords: Data mining, computer.software_genre, computer, Genetic algorithm, Tabu search, Support vector machine, Engineering, business.industry, business, Mean squared error, Kernel (statistics), Mean absolute percentage error, Hilbert–Huang transform, Error function, ice cover prediction, adaptive support vector machine (ASVM), genetic tabu search (GATS), two-stage data processing, ensemble empirical mode decomposition, fast independent component analysis, Technology, T
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