• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

ELECTRIC POWER CONSTRUCTION ›› 2015, Vol. 36 ›› Issue (3): 27-32.doi: 10.3969/j.issn.1000-7229.2015.03.005

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Mountain Fire Spread Speed Combined Forecasting Model for Transmission Line Based on EMD and ELM

LI Jinwei1, WANG Qi1, HE Hongtai2, PEI Guanrong2   

  1. 1. Maintenance & Test Centre, CSG EHV Power Transmission Company, Guangzhou 510663, China; 2. Beijing Guowang Fuda
    Science&Technology Development Co., Ltd., Beijing 100070, China
  • Online:2015-03-01

Abstract:

 According to the impact of mountain fire of transmission line in complex environment, the mountain fire prediction model was proposed based on the methods of empirical mode decomposition (EMD) and extreme learning machine (ELM). Firstly, the noise of collected wind speed time series was analyzed by using wavelet transform, and the classification and reconstruction were carried out according to the different sequences, in order to reconstruct new wind speed time series. Secondly, the factors of the mountain fire were decomposed into a series of sub-sequences with different characteristics scales by using EMD. Thirdly, cross-validation method and phase space reconstruction method were used to determine various parameters and input dimensions of machine learning, and then the modeling and forecasting analysis was carried out for the mountain fire of transmission line by using ELM. The simulation results show that the combined forecasting model for the mountain fire of transmission lines based on EMD and ELM can effectively predict fire spread speed within 24 h, which can provide the possibility to realize the online prediction of the mountain fire in transmission line with high precision.

Key words: mountain fire, empirical mode decomposition(EMD), multi-resolution analysis, extreme learning machine(ELM)