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Predicting energy consumption in multiple buildings using machine learning for improving energy efficiency and sustainability

  • Published:2020-07 Issue: Volume:260 Page:121082
  • ISSN:0959-6526
  • Container-title:Journal of Cleaner Production
  • language:en
  • Short-container-title:Journal of Cleaner Production

Author:

Pham Anh-Duc,Ngo Ngoc-Tri,Ha Truong Thi Thu,Huynh Nhat-To,Truong Ngoc-Son

Funder

Vingroup Innovation Foundation

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Strategy and Management,General Environmental Science,Renewable Energy, Sustainability and the Environment

Reference28 articles.

1. Predicting energy demand peak using M5 model trees;Abdelkader,2015

2. Energy consumption and efficiency in buildings: current status and future trends;Allouhi;J. Clean. Prod.,2015

3. A review of data-driven building energy consumption prediction studies;Amasyali;Renew. Sustain. Energy Rev.,2018

4. Random Forests;Breiman,2001

5. Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery;Chan;Rem. Sens. Environ.,2008
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