Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature

Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature

The accurate estimation of dew point temperature (Tdew) is important in climatological, agricultural, and agronomical studies. In this study, the feasibility of two soft computing methods, random forest (RF) and multivariate adaptive regression splines (MARS), is evaluated for predicting the long-te...

Full description

Bibliographic Details
Main Authors: Guodao Zhang, Sayed M. Bateni, Changhyun Jun, Helaleh Khoshkam, Shahab S. Band, Amir Mosavi
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Environmental Science
Subjects:
dew point temperature
random forest
multivariate adaptive regression splines
machine learning
big data
artificial intelligence
Online Access:https://www.frontiersin.org/articles/10.3389/fenvs.2022.826165/full

Internet

https://www.frontiersin.org/articles/10.3389/fenvs.2022.826165/full

Similar Items