A genetic programming-based model for predicting phosphorus concentration in shallow lakes

被引：1
|
作者：
Bai, Yu [1 ]
Yang, Jianquan [2 ]
Sun, Guojin [1 ]
Zhao, Yufeng [1 ]
Yu, Yu [1 ]
机构：
[1] Zhejiang Univ Water Resources & Elect Power, Hangzhou 310000, Zhejiang, Peoples R China
[2] Natl Water Museum China, Hangzhou, Peoples R China
来源：
WATER PRACTICE AND TECHNOLOGY | 2022年 / 17卷 / 03期
关键词：
genetic programming-based model; shallow lakes; temperature; total phosphorus; wind speed; TAIHU LAKE; PARTICULATE PHOSPHORUS; AQUATIC SEDIMENTS; WATER INTERFACE; RELEASE; NITROGEN; DYNAMICS; EUTROPHICATION; TEMPERATURE; CYANOBACTERIA;
D O I：
10.2166/wpt.2022.023
中图分类号：
TV21 [水资源调查与水利规划];
学科分类号：
081501 ;
摘要：
In this study, a large amount of lake monitoring data was collected and genetic programming, a machine learning technique based on natural selection, was used to search for a robust relationship between phosphorus concentration, wind speed and water temperature. No forms were specified before searching but a new prediction formula was obtained. The formula can provide acceptable simulation accuracy and a theoretical reference for water environment management in shallow lakes or reservoirs.
引用
收藏
页码：637 / 644
页数：8
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