Abstract
Hydroelectric power plants are an important source of electricity in the world, but at the same time they can face various emergency situations that can lead to significant economic and environmental consequences. Recently, neural networks have become an increasingly popular tool for modeling and predicting emergency situations at hydroelectric power plants. This article discusses approaches to assessing the consequences of possible accidents at northern hydraulic structures. To develop scenarios and models, the Toxy + risk software and analytical complex and recurrent neural networks developed in the python programming language were used in the work. Various scenarios for the development of emergency situations have been developed and an assessment of the risk of their occurrence has been made.
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