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Using long short-term memory networks to predict energy consumption of air-conditioning systems

  • Published:2020-04 Issue: Volume:55 Page:102000
  • ISSN:2210-6707
  • Container-title:Sustainable Cities and Society
  • language:en
  • Short-container-title:Sustainable Cities and Society

Author:

Zhou Chonggang,Fang Zhaosong,Xu Xiaoning,Zhang Xuelin,Ding Yunfei,Jiang Xiangyang,ji Ying

Funder

National Key R&D Program of China

Guangzhou Science and Technology Plan Project

Publisher

Elsevier BV

Subject

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

Reference55 articles.

1. Forecasting monthly electric energy consumption in eastern Saudi Arabia using univariate time-series analysis;Abdelaal;Energy,2014

2. Short-term hourly load forecasting using time-series modeling with peak load estimation capability;Amjady;IEEE Transactions on Power Systems,2001

3. Forecasting malaria incidence based on monthly case reports and environmental factors in karuzi, burundi, 1997–2003;Armando;Malaria Journal,2007

4. Prediction of residential building energy consumption: A neural network approach;Biswas;Energy,2016
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