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- Article name
- Exploratory analysis of the composition and properties of river water using neural network techniques
- Authors
- ROSENTHAL O. M., , omro3@yandex.ru, Institute of Water Problems of the Russian Academy of Sciences, Moscow, Russia
FEDOTOV V. Kh., , fvh@inbox.ru, I. N. Ulyanov Chuvash State University, Cheboksary, Russia
- Keywords
- quality / control of water composition / industrial discharges / water footprint / hydrochemical gate / artificial neural networks / neural network analysis
- Year
- 2023 Issue 1 Pages 46 - 50
- Code EDN
- NVGYRP
- Code DOI
- 10.52190/2073-2589_2023_1_46
- Abstract
- Exploratory analysis of hydrological and hydrochemical characteristics of water in streams using neural network research techniques were performed. For this purpose, time series of hydrochemical indicators of the water quality of the Iset River in the Yekaterinburg area were monitored. The results obtained indicate a neural network correlation linking the concentration of individual impurities in water reaching 0.9, and linking water consumption with its quality indicators reaching 0.4. The high weights of the neural connections of the studied systems and the correlations found indicate the expediency of revising the well-established ideas about the behavior of pollutants of the water stream as a passive component carried away by the current, indicate the processes of microstructural self-organization occurring here and the possibility of predicting the composition of the properties of river water by neural network methods. The information received, in addition to its direct purpose in terms of knowledge of the nature and properties of water resources, is a necessary condition for effective management of their quality and sustainable water management.
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