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Comparison of four bio-inspired algorithms to optimize KNEA for predicting monthly reference evapotranspiration in different climate zones of China

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成果类型:
期刊论文
作者:
Dong, Jianhua;Liu, Xiaogang;Huang, Guomin;Fan, Junliang;Wu, Lifeng;...
通讯作者:
Wu, Lifeng(china.sw@163.com)
作者机构:
[Dong, Jianhua; Huang, Guomin; Wu, Lifeng] Nanchang Inst Technol, Sch Hydraul & Ecol Engn, Nanchang 330099, Jiangxi, Peoples R China.
[Liu, Xiaogang] Kunming Univ Sci & Technol, Fac Agr & Food, Kunming 650500, Yunnan, Peoples R China.
[Fan, Junliang] Northwest A&F Univ, Key Lab Agr Soil & Water Engn Arid & Semiarid Are, Minist Educ, Yangling 712100, Shaanxi, Peoples R China.
[Wu, Jie] Wuhan Polytech Univ, Sch Civil Engn & Architecture, Wuhan 430023, Peoples R China.
通讯机构:
[Lifeng Wu] S
School of Hydraulic and Ecological Engineering, Nanchang Institute of Technology, Nanchang 330099, China
语种:
英文
关键词:
Climatic zones;Grasshopper optimization algorithm;Grey wolf optimization algorithm;Machine learning;Reference evapotranspiration
期刊:
Computers and Electronics in Agriculture
ISSN:
0168-1699
年:
2021
卷:
186
页码:
106211
基金类别:
This study was jointly supported by the Science and Technology Project of Jiangxi Provincial Department of Education (GJJ170981) and the Chinese National Natural Science Fund (51709143, 51769010 and 51979133). Thanks to the National Meteorological Information Center of China Meteorological Administration for offering the meteorological data.
机构署名:
本校为其他机构
院系归属:
土木工程与建筑学院
摘要:
Accurate estimation of reference crop evapotranspiration (ET0) is of great significance to crop water use and agricultural water resources management. This study evaluated the performance of four bio-inspired algorithm optimized kernel-based nonlinear extension of Arps decline (KNEA) models, namely KNEA with grasshopper optimization algorithm (GOA-KNEA), KNEA with grey wolf optimizer algorithm (GWO-KNEA), KNEA with particle swarm optimization algorithm (PSO-KNEA), and KNEA with salp swarm algorithm (SSA-KNEA), on estimating monthly ET0 across C...

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