Application of ensemble learning techniques to model the atmospheric concentration of SO2

A. Masih

Volume 5, Issue 3 , July 2019, , Pages 309-318

https://doi.org/10.22034/GJESM.2019.03.04

Abstract
  In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single ...  Read More