Forecasting of Electricity Consumption for G20 Members Using Various Machine Learning Techniques-Reference-Cited by-同舟云学术

Forecasting of Electricity Consumption for G20 Members Using Various Machine Learning Techniques

Published:2022-02-07 Issue: Volume: Page:211-227
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Container-title:Artificial Intelligence for Renewable Energy Systems
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Author:

Suhagiya Jaymin,Raval Deep,Pandey Siddhi Vinayak,Patel Jeet,Gupta Ayushi,Srivastava Akshay

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119761686.ch10

Reference26 articles.

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4. Wang Z. Li J. Zhu S. Zhao J. Deng S. Shengyuan Z. Yin H. Li H. Qi Y. Gan Z. A review of load forecasting of the distributed energy system. IOP Conference Series: Earth and Environmental Science 03 2019 vol. 237 p. 042019.

5. Alagbe V. Popoola S.I. Atayero A.A. Adebisi B. Abolade R.O. Misra S. Artificial intelligence techniques for electrical load forecasting in smart and connected communities in: International Conference on Computational Science and Its Applications Springer pp.219–230 2019.

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