| Issue |
E3S Web of Conf.
Volume 381, 2023
International Scientific and Practical Conference “Development and Modern Problems of Aquaculture” (AQUACULTURE 2022)
|
|
|---|---|---|
| Article Number | 01036 | |
| Number of page(s) | 9 | |
| Section | Agriculture, River Ecosystems and Environment | |
| DOI | https://doi.org/10.1051/e3sconf/202338101036 | |
| Published online | 14 April 2023 | |
Hydroecological data recovery using artificial intelligence
Ufa University of Science and Technology, 32, Zaki Walidi street, Ufa, 450076. Russia
* Corresponding author: ashaniyazova@bk.ru
Artificial neural networks and genetic algorithms have been tested for the restoration of missed hydroecological indicators (hydrological water quality parameters and bottom sediment quality parameters). Algorithms have been developed for recovering missing hydroecological data in the presence and absence of observation data from points upstream and downstream. Neural network models for the restoration of water quality indicators and bottom sediments were tested on the example of the catchment basin of the Bayda and Kidysh rivers in the territory of the Republic of Bashkortostan.
© The Authors, published by EDP Sciences, 2023
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