A Comparative study of three AI prediction algorithms based on measured databases for an optimal Smart Grid-Reference-Cited by-同舟云学术

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A Comparative study of three AI prediction algorithms based on measured databases for an optimal Smart Grid

Published:2022-05-17 Issue: Volume: Page:
ISSN:
Container-title:2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)
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Author:

Naceur Ferdaws Ben¹,Telmoudi Achraf Jabeur²,Mahjoub Mohamed Ali³

Affiliation:

1. University of Sousse,ISITCom,Sousse,Tunisia,4011

2. University of Tunis, Higher National Engineering School of Tunis,LISIER Lab.,Tunis,Tunisia,1008

3. University of Sousse, National Engineering School of Sousse,LATIS - Laboratory of Advanced Technology and Intelligent Systems,Sousse,Tunisia,4023

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9803856/9803880/09804155.pdf?arnumber=9804155

Reference24 articles.

1. The implementation of univariable scheme-based air temperature for solar radiation prediction: New development of dynamic evolving neural-fuzzy inference system model

2. A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting

3. A novel soft computing framework for solar radiation forecasting

4. An artificial neural network-based forecasting model of energy-related time series for electrical grid management;di;Mathematics and Computers in Simulation,2020

5. Intelligent approach for optimal sizing in photovoltaic panel-battery system and optimizing smart grid energy

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