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

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.