Enhancing Solar Radiation Prediction for Computational-Constrained Environments Using Hybrid Artificial Neural Networks

Enhancing Solar Radiation Prediction for Computational-Constrained Environments Using Hybrid Artificial Neural Networks

This paper presents a hybrid predictive model optimized for resource-constrained environments, focusing on renewable energy systems in remote areas. The model integrates various Artificial Neural Network (ANN) architectures—Multilayer Perceptron (MLP), Convolutional Neural Networks (CNN),...

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Bibliographic Details
Main Authors: D. O. Cardozo, B. Medina, C. Quintero, M. Pardo
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Renewable energy
predictive modeling
artificial neural networks (ANN)
resource-constrained environments
distributed generation
solar radiation prediction
Online Access:https://ieeexplore.ieee.org/document/10811916/

Internet

https://ieeexplore.ieee.org/document/10811916/

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