Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration

Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration

Abstract For developing countries, scarcity of climatic data is the biggest challenge, and model development with limited meteorological input is of critical importance. In this study, five data intelligent and hybrid metaheuristic machine learning algorithms, namely additive regression (AR), AR-bag...

Full description

Bibliographic Details
Main Authors: Ahmed Elbeltagi, Ali Raza, Yongguang Hu, Nadhir Al-Ansari, N. L. Kushwaha, Aman Srivastava, Dinesh Kumar Vishwakarma, Muhammad Zubair
Format: Article
Language:English
Published: SpringerOpen 2022-05-01
Series:Applied Water Science
Subjects:
Reference evapotranspiration
Additive regression
Sensitivity and regression analysis
Machine learning
Hydrological modeling
Online Access:https://doi.org/10.1007/s13201-022-01667-7

Internet

https://doi.org/10.1007/s13201-022-01667-7

Similar Items