A review on machine learning forecasting growth trends and their real-time applications in different energy systems-Reference-Cited by-同舟云学术

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A review on machine learning forecasting growth trends and their real-time applications in different energy systems

Published:2020-03 Issue: Volume:54 Page:102010
ISSN:2210-6707
Container-title:Sustainable Cities and Society
language:en
Short-container-title:Sustainable Cities and Society

Author:

Ahmad Tanveer,Chen Huanxin

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

Reference256 articles.

1. Forecasting monthly electric energy consumption in eastern Saudi Arabia using univariate time-series analysis;Abdel-Aal;Energy,1997

2. A novel ANN-based approach to estimate heat transfer coefficients in radiant wall heating systems;Acikgoz;Energy and Buildings,2017

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

4. Utility companies strategy for short-term energy demand forecasting using machine learning based models;Ahmad;Sustainable Cities and Society,2018

5. Nonlinear autoregressive and random forest approaches to forecasting electricity load for utility energy management systems;Ahmad;Sustainable Cities and Society,2019

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