| Issue |
BIO Web Conf.
Volume 130, 2024
International Scientific Conference on Biotechnology and Food Technology (BFT-2024)
|
|
|---|---|---|
| Article Number | 03001 | |
| Number of page(s) | 7 | |
| Section | Water Environmental Biotechnology | |
| DOI | https://doi.org/10.1051/bioconf/202413003001 | |
| Published online | 09 October 2024 | |
Analyzing the influence of parameters on water quality using logistic regression
1 Bauman Moscow State Technical University (BMSTU), 105005 Moscow, Russia
2 Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia
3 Russian State Agrarian University - Timiryazev Moscow Agricultural Academy (RSAU-MAA Named after K.A. Timiryazev, 127550 Moscow, Russia
* Corresponding author: anna_glinskaja@rambler.ru
This article explores the application of machine learning techniques to analyze and evaluate water quality. In particular, the article focuses on the use of logistic regression to identify and analyze key parameters affecting the potability of water. The application of logistic regression in water quality analysis not only allows us to build models for prediction, but also to formulate recommendations for improving water treatment and monitoring processes. As a result, the resulting data and models can be used to develop strategies to provide safe drinking water, which is important for the health and well-being of the community. Thus, the article proposes a modern approach to analyzing water quality using logistic regression, which allows for a deeper understanding of the relationships between water parameters and its potability, as well as the development of effective methods for water quality management.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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