Prediction of electricity energy consumption including <scp>COVID</scp> ‐19 precautions using the hybrid <scp>MLR‐FFANN</scp> optimized with the stochastic fractal search with fitness distance balance algorithm-Reference-Cited by-同舟云学术

Prediction of electricity energy consumption including COVID ‐19 precautions using the hybrid MLR‐FFANN optimized with the stochastic fractal search with fitness distance balance algorithm

Published:2022-03-22 Issue:15 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Dalcali Adem¹,Özbay Harun²,Duman Serhat²^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering, Faculty of Engineering and Natural Sciences Bandirma Onyedi Eylul University Bandirma Turkey

2. Department of Electrical Engineering, Faculty of Engineering and Natural Sciences Bandirma Onyedi Eylul University Bandirma Turkey

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6947

Reference68 articles.

1. Electricity demand during pandemic times: The case of the COVID-19 in Spain

2. Effects of COVID-19 on electric energy consumption in Turkey and ANN-based short-term forecasting

3. An overview of electricity demand forecasting techniques;Singh AK;Netw Complex Syst,2013

4. Power demand forecasting for demand-driven energy production with biogas plants

5. IslamM MaitiM SanyalJ.Regression‐based predictive models for estimation of electricity consumption. Proceedings of the International Conference on Sustainable Development; 2019:59‐62.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimal Power Flow for Hybrid AC/DC Electrical Networks Configured With VSC-MTDC Transmission Lines and Renewable Energy Sources;IEEE Systems Journal;2023-09

2. A Methodology for Energy Usage Prediction in Long-Lasting Abnormal Events;2022 IEEE 4th International Conference on Cognitive Machine Intelligence (CogMI);2022-12