Modelagem preditiva de parâmetros da qualidade da água do Parque das Águas de Cuiabá por meio de programação genética

Abstract

Water quality is a fundamental indicator for environmental preservation and public health, requiring constant monitoring and effective analysis methods. Therefore, it becomes relevant to develop predictive models capable of accurately and autonomously estimating important parameters. This work aims to perform a predictive modeling to derive equations from water quality parameter data collected at Parque das Águas in Cuiabá, using genetic programming — an artificial intelligence technique inspired by evolutionary processes. The model seeks to generate mathematical expressions that describe the behavior of the variables in a way that appropriately represents the dataset. The results are expected to contribute to the efficient monitoring of water quality in urban environments and to encourage the use of evolutionary approaches in environmental applications.