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

详细信息    查看全文

• 作者：Qidong Yang^a ; ^{yangqd@ynu.edu.cn} ; Jian Wu^a ; Yueqing Li^b ; Weidong Li^a ; Lijuan Wang^c ; Yang Yang^c
• 关键词：Maqu station ; Monin-Obukhov similarity theory ; Particle swarm optimization algorithm ; Source region of the Yellow River
• 刊名：Agricultural and Forest Meteorology
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：232
• 期：Complete
• 页码：606-622
• 全文大小：2010 K
• 卷排序：232

文摘

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.