Artificial intelligence and modelling in hydrobiological research

Abstract

Information technology is essential for the advancement of science. Every day, scientists across all fields face overwhelming data volumes that exceed manual processing capabilities. Mathematical models and artificial intelligence (AI) are introduced as a necessary component for processing environmental information. Environmental AI is used mainly for environmental monitoring, hazard toxicology forecasting, and robotic systems aimed at high sampling depth accuracy. A comparative analysis of convolution neural network (CNN) models shows their potential for successful identification of algal species with sufficient illustrative data for successful machine learning. We systematized the application of modern research methods using AI and mathematical modeling in hydrobiology.