Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm-Reference-Cited by-同舟云学术

Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm

Published:2024-10 Issue: Volume:136 Page:109034
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Kaplan Yusuf Alper

Publisher

Elsevier BV

Reference40 articles.

1. Daily global solar radiation time series prediction using variational mode decomposition combined with multi-functional recurrent fuzzy neural network and quantile regression forests algorithm;Abdallah;Energy Rep.,2023

2. A hybrid Harris Hawks optimization algorithm with simulated annealing for feature selection;Abdel-Basset;Artif. Intell. Rev.,2021

3. Prediction of daily global solar radiation using different machine learning algorithms: evaluation and comparison;Ağbulut;Renew. Sustain. Energy Rev.,2021

4. Estimated monthly average global radiation for Turkey and its comparison with observations;Aksoy;Renew. Energy,1997

5. An artificial intelligence-based solar radiation prophesy model for green energy utilization in energy management system;Alassery;Sustain. Energy Technol. Assessments,2022

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. Artificial Intelligence-Based Improvement of Empirical Methods for Accurate Global Solar Radiation Forecast: Development and Comparative Analysis;Energies;2024-08-28

2. Sunspot number-based neural network model for global solar radiation estimation in Ghardaïa;STUDIES IN ENGINEERING AND EXACT SCIENCES;2024-08-27