Optimization of extreme learning machine model with biological heuristic algorithms to estimate daily reference evapotranspiration in Hetao Irrigation District of China-Reference-Cited by-同舟云学术

Optimization of extreme learning machine model with biological heuristic algorithms to estimate daily reference evapotranspiration in Hetao Irrigation District of China

Published:2022-09-22 Issue:1 Volume:16 Page:1939-1956
ISSN:1994-2060
Container-title:Engineering Applications of Computational Fluid Mechanics
language:en
Short-container-title:Engineering Applications of Computational Fluid Mechanics

Author:

He Huaijie¹,Liu Ling¹²,Zhu Xiuqun¹

Affiliation:

1. College of Hydrology and Water Resources, Hohai University, Nanjing, People’s Republic of China

2. State Key Laboratory of Hydrology Water Resources and Hydraulic Engineering, Hohai University, Nanjing, People’s Republic of China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Informa UK Limited

Subject

Modeling and Simulation,General Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/19942060.2022.2125442

Reference45 articles.

1. A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration

2. Swarm-based optimization as stochastic training strategy for estimation of reference evapotranspiration using extreme learning machine

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