Integrating experimental and theoretical approaches for enhanced machine learning modeling of solar radiation
This study presents a novel hybrid framework for estimating solar radiation components—critical for optimizing solar energy systems—by integrating theoretical solar parameters with meteorological data, an approach seldom explored in literature. A one-year dataset, recorded at 15-minute intervals, wa...
Saved in:
| Main Authors: | Nader Ghareeb, Abeer Alanazi, Ahmad Sedaghat, Mohamad Hussein Farhat, Arash Mehdizadeh, Hayder Salem, Mohammad Nazififard, Ali Mostafaeipour |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
|
| Series: | Engineering Science and Technology, an International Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215098625002113 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Efficient Machine Learning Models for Solar Radiation Prediction Using Ensemble Techniques: A Case Study in Low-Rainfall Arid Climates
by: Jimmy Aurelio Rosales Huamani, et al.
Published: (2025-01-01) -
Experimental study of the effect of meteorological parameters on the performance of the solar chimney power plant
by: Abdelghani Aziz, et al.
Published: (2021-06-01) -
Prediction of Global, Diffused and Direct Solar Radiation for Oriented and Inclined Surface Based on Meteorological Data for efficient energy use in the south of Tunisia
by: mahmoud ben amara, et al.
Published: (2022-03-01) -
The Impact of Meteorological Data on the Accuracy of Solar Electricity Generation Forecasting Using Neural Networks
by: Yuriy Sayenko, et al.
Published: (2025-04-01) -
Effects of Window Films in Thermo-Solar Properties of Office Buildings in Hot-Arid Climates
by: Ahmad Sedaghat, et al.
Published: (2021-05-01)