Comparative Analysis of Prediction on Solar Radiation in Energy Generation System using Random Forest and Decision Tree

The solar radiation estimation is very important for developing and design of solar energy production system in generation of non-renewable energy. But the data set of Global solar radiation is not easily obtainable in all places of India due to some technical issues and cost in measurement technolo...

Full description

Saved in:
Bibliographic Details
Published in2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) pp. 899 - 903
Main Authors P, Sasirekha, T M, Navinkumar, Praveen A, Anton Amala, T, Bharani Prakash, P, Swapna, Vinothkumar, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.04.2022
Subjects
Machine learning algorithms
Prediction algorithms
Predictive Analysis
Random Forest
Regression Tree
Solar radiation
Solar radiation prediction
Support vector machines
Temperature measurement
Training
Wind speed
Online AccessGet full text
DOI10.1109/ICSCDS53736.2022.9760819

Cover

More Information
Summary:The solar radiation estimation is very important for developing and design of solar energy production system in generation of non-renewable energy. But the data set of Global solar radiation is not easily obtainable in all places of India due to some technical issues and cost in measurement technologies. Consequently it is important to forecasting the solar radiation prediction using some techniques by input parameters namely Time, Radiation, Temperature, Pressure, Humidity, Wind Direction, Speed, Time Sun rise and Time sun set. In this paper the author focused on analyzing the solar radiation prediction using Random Forest technique. This analysis gives more clear knowledge in prediction performance using machine learning algorithms.
DOI:10.1109/ICSCDS53736.2022.9760819