Analysis of hourly cooling load prediction accuracy with data-mining approaches on different training time scales-Reference-Cited by-同舟云学术

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Analysis of hourly cooling load prediction accuracy with data-mining approaches on different training time scales

Published:2019-11 Issue: Volume:51 Page:101717
ISSN:2210-6707
Container-title:Sustainable Cities and Society
language:en
Short-container-title:Sustainable Cities and Society

Author:

Fan Chengliang,Ding Yunfei,Liao Yundan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Transportation,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering,Geography, Planning and Development

Reference45 articles.

1. Short and medium-term forecasting of cooling and heating load demand in building environment with data-mining based approaches;Ahmad;Energy and Buildings,2018

2. A review on applications of ANN and SVM for building electrical energy consumption forecasting;Ahmad;Renewable and Sustainable Energy Reviews,2014

3. Accounting frameworks for tracking energy efficiency trends;Ang;Energy Economics,2010

4. Multiple regression models to predict the annual energy consumption in the Spanish banking sector;Aranda;Energy and Buildings,2012

5. ASHRAE handbook-fundamentals (SI);ASHRAE,2011

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