Development of Predictive Model for Radon-222 Estimation in the Atmosphere using Stepwise Regression and Grid Search Based-Random Forest Regression

Development of Predictive Model for Radon-222 Estimation in the Atmosphere using Stepwise Regression and Grid Search Based-Random Forest Regression

This work develops predictive models for estimating radon (222Rn) activity concentration in the atmosphere using novel grid search based random forest regression (GS-RFR) and stepwise regression (SWR). The developed models employ meteorological parameters which include the temperature, pressure, re...

Full description

Bibliographic Details
Main Authors: Omodele Olubi, Ebeneze Oniya, Taoreed Owolabi
Format: Article
Language:English
Published: Nigerian Society of Physical Sciences 2021-05-01
Series:Journal of Nigerian Society of Physical Sciences
Subjects:
radon
machine learning
meteorological parameters
atmosphere
Online Access:https://journal.nsps.org.ng/index.php/jnsps/article/view/177

Internet

https://journal.nsps.org.ng/index.php/jnsps/article/view/177

Similar Items