Electric load forecasting by the SVR model with differential empirical mode decomposition and auto regression-Reference-Cited by-同舟云学术

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Electric load forecasting by the SVR model with differential empirical mode decomposition and auto regression

Published:2016-01 Issue: Volume:173 Page:958-970
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Fan Guo-Feng,Peng Li-Ling,Hong Wei-Chiang^ORCID,Sun Fan

Funder

Startup Foundation for Doctors

Educational Commission of Henan Province of China

The Youth Foundation of Ping Ding Shan University

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference32 articles.

1. A pseudo-panel data model of household electricity demand;Bernard;Resour. Energy Econ.,2010

2. Long-term electrical energy consumption forecasting for developing and developed economies based on different optimized models and historical data types;Ardakani;Energy,2014

3. Estimating industrial and residential electricity demand in Turkey: A time varying parameter approach;Arisoy;Energy,2014

4. Data analysis and short term load forecasting in Iran electricity market using singular spectral analysis (SSA);Afshar;Energy,2011

5. Time series models (Grey–Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India;Kumar;Energy,2010

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