Using the particle swarm optimization algorithm to calibrate the parameters relating to the turbulent flux in the surface layer in the source region of the Yellow River

•Particle swarm optimization algorithm was introduced to the MOST for calibrating the parameters.•The differences between calculations used the calibrated parameters and observations were rather small.•PSO algorithm is a stable and efficient approach which can be applied in MOST parameter estimation...

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Bibliographic Details
Published in:	Agricultural and forest meteorology Vol. 232; pp. 606 - 622
Main Authors:	Yang, Qidong, Wu, Jian, Li, Yueqing, Li, Weidong, Wang, Lijuan, Yang, Yang
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 15.01.2017
Subjects:	algorithms artificial intelligence climate correlation energy equations Freshwater heat hydrologic cycle Maqu station mathematical models methodology momentum Monin-Obukhov similarity theory Particle swarm optimization algorithm problem solving roughness Source region of the Yellow River Yellow River China, People's Rep., Huang He R Yellow River Source region of the Yellow River Monin-Obukhov similarity theory Maqu station Particle swarm optimization algorithm
ISSN:	0168-1923, 1873-2240
Online Access:	Get full text
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