Estimating Solar Energy within the scope of environmental factors by the Neural Network algorithm

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

Mühendislik Bilimleri ve Araştırmaları Dergisi
Volume:6 Issue:1
Estimating Solar Energy within the scope of environmental factors by the Neural Network algorithm

Estimating Solar Energy within the scope of environmental factors by the Neural Network algorithm

Pages : 24-34

View : 84 | Download : 94

Publication Date : 2024-04-30

Article Type : Research Paper

Abstract :The efficiency of solar energy systems requires a complicated forecasting process due to the variability of sunlight and environmental conditions. Among environmental factors, cloud coverage (% range), temperature (0C), wind speed (Mph), and humidity (%) variables were taken into account in this study. Neural networks (NN), which are machine learning (ML) algorithms with a flexible structure that can define complex relationships and process large amounts of data for solar energy prediction, were used in this study. The NN algorithm showed a high performance, with mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2) values calculated as 0.019, 0.139, 0.053, and 0.977, respectively. This study emphasized that solar energy predictions made with the NN algorithm, considering environmental factors, are an essential tool that helps use solar energy systems more efficiently and sustainably.
Keywords : Makine Öğrenimi, Sinir Ağı Algoritması, Güneş Enerjisi, Çevresel Faktörler

ORIGINAL ARTICLE URL

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.