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Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review

  • Published:2017-04 Issue: Volume:70 Page:1108-1118
  • ISSN:1364-0321
  • Container-title:Renewable and Sustainable Energy Reviews
  • language:en
  • Short-container-title:Renewable and Sustainable Energy Reviews

Author:

Mat Daut Mohammad Azhar,Hassan Mohammad Yusri,Abdullah Hayati,Rahman Hasimah Abdul,Abdullah Md Pauzi,Hussin Faridah

Funder

Research University Grant (GUP)

Publisher

Elsevier BV

Subject

Renewable Energy, Sustainability and the Environment

Reference100 articles.

1. The World Factbook 2013–14. Washington, D.C.I.A; 2013. Available from: 〈https://www.cia.gov/library/publications/the-world-factbook/index.html〉.

2. A review of thermodynamics and heat transfer in solar refrigeration system;Afshar;Renew Sustain Energy Rev,2012

3. Power load forecasting using support vector machine and ant colony optimization;Niu;Expert Syst Appl,2010

4. New artificial neural network prediction method for electrical consumption forecasting based on building end-uses;Escrivá-Escrivá;Energy Build,2011

5. Solar radiation forecast based on fuzzy logic and neural networks;Chen;Renew Energy,2013

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