Unveiling the SALSTM-M5T model and its python implementation for precise solar radiation prediction-Reference-Cited by-同舟云学术

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Unveiling the SALSTM-M5T model and its python implementation for precise solar radiation prediction

Published:2023-11 Issue: Volume:10 Page:3402-3417
ISSN:2352-4847
Container-title:Energy Reports
language:en
Short-container-title:Energy Reports

Author:

Ehteram Mohammad,Shabanian Hanieh^ORCID

Publisher

Elsevier BV

Subject

General Energy

Reference56 articles.

1. Exploring Bayesian model averaging with multiple ANNs for meteorological drought forecasts;Achite;Stoch. Environ. Res. Risk Assess.,2022

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

3. Improving the accuracy of daily solar radiation prediction by climatic data using an efficient hybrid deep learning model: Long short-term memory (LSTM) network coupled with wavelet transform;Alizamir;Eng. Appl. Artif. Intell.,2023

4. Time series ARIMA model for predicting daily and monthly average global solar radiation: the Seoul, South Kor;Alsharif;Symmetry,2019

5. Deep learning models for long-term solar radiation forecasting considering microgrid installation: a comparative study;Aslam;Energies,2019

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1. Application of wavelet and seasonal-based emotional ANN (EANN) models to predict solar irradiance;Energy Reports;2024-12

2. Probabilistic forecasting of regional solar power incorporating weather pattern diversity;Energy Reports;2024-06

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