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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Vydáno v:	Agricultural and forest meteorology Ročník 232; s. 606 - 622
Hlavní autoři:	Yang, Qidong, Wu, Jian, Li, Yueqing, Li, Weidong, Wang, Lijuan, Yang, Yang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 15.01.2017
Témata:	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
On-line přístup:	Získat plný text
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