APPROACHING VARIOUS DATA CLASSIFICATION METHODS IN WATER QUALITY FORECASTING

Abstract

Water quality is an important issue because of its relationship with humans and other living organisms in the natural world. The problem at hand is how to accurately predict water quality parameters in order to ensure the high effectiveness of water resource management. Additionally, in practice, there are currently no solutions applying classification techniques based on deep learning models in the field of water resource management. Based on the aforementioned practices, in this paper, the authors introduce an approach using classification techniques such as SVM, Random Forest, Logistic Regression. The experimental results of the paper show that the CNN deep learning model proposed by the authors has higher accuracy compared to other traditional classification methods.