A hybrid optimized model for predicting evapotranspiration in early and late rice based on a categorical regression tree combination of key influencing factors

•The ETC model based on key factors is proposed for early and late rice.•Rn shows the highest correlation with early and late rice evapotranspiration.•The SSA-LSSVM model performs best among the optimization models. Crop evapotranspiration (ETC) is an important component of the agricultural hydrolog...

Full description

Saved in:

Bibliographic Details
Published in:	Computers and electronics in agriculture Vol. 211; p. 108031
Main Authors:	Zhao, Long, Qing, Shunhao, Bai, Jiayi, Hao, Haohao, Li, Hui, Shi, Yi, Xing, Xuguang, Yang, Ru
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.08.2023
Subjects:	agriculture Categorical Regression Tree electronics Evapotranspiration hybrids hydrologic cycle irrigation leaf area index Least Squares Support Vector Machine Meta-heuristic optimization algorithms prediction regression analysis Rice soil water solar radiation support vector machines temperature wind speed Least Squares Support Vector Machine Categorical Regression Tree Meta-heuristic optimization algorithms Evapotranspiration Rice
ISSN:	0168-1699, 1872-7107
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!