A genetic programming-based model for predicting phosphorus concentration in shallow lakes. Issue 3 (16th March 2022)

• Record Type: Journal Article
• Authors: Bai, Yu; Yang, Jianquan; Sun, Guojin; Zhao, Yufeng; Yu, Yu
• Is Part Of: Water practice and technology. Volume 17:Issue 3(2022)
• Page Start: 637
• Page End: 644
• Publication Date: 2022-03-16
• Subjects: genetic programming-based model -- shallow lakes -- temperature -- total phosphorus -- wind speed; Sewerage; Sewerage -- Management; Water-supply; Water-supply engineering; Periodicals; 628.205
• DOI: 10.2166/wpt.2022.023
• Languages: English
• ISSNs: 1751-231X

Abstract

Abstract: 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. HIGHLIGHT: A genetic programming-based model for predicting TP concentration. Graphical Abstract