Forecasting the environmental safety of water resources using neural networks

¹ Bauman Moscow State Technical University, 2-ya Baumanskaya st., 5, building 1, 105005, Moscow, Russia
² Reshetnev Siberian State University of Science and Technology, Krasnoyarsk Rabochy Ave., 31, 660037, Krasnoyarsk, Russia

^* Corresponding author: sofaglu2000@mail.ru

Abstract

In this study, a neural network model has been developed to analyze the suitability of water based on its chemical and physical characteristics. The ecological significance of the task is due to the need for effective monitoring of the quality of water resources, which are an essential element of ecosystems and directly affect human health and the environment. The model has demonstrated a high accuracy of 87%, which confirms its effectiveness for automated analysis of water quality. The results of the study indicate the importance of parameters such as pH and concentration of pollutants for determining the suitability of water. The developed model can be implemented into environmental monitoring systems, providing more rapid and accurate detection of pollution and improving decision-making processes in water resources management.