This article examines methods of analyzing water composition and the possibilities of using modern technologies. The study compared traditional physical, chemical, and biological methods of water quality assessment, as well as measurements performed using sensor technologies. The possibility of quickly and accurately determining water parameters using devices such as the Exo2 sonde and TDS sensor was considered. In addition, it was shown that artificial intelligence-based algorithms can classify water samples in water quality assessment and analysis, evaluate them according to different parameters, and group them into categories. The application of Decision Tree, Random Forest, and SVM models was also analyzed. The results of the study examined the possibilities of using water monitoring systems as an effective tool that increases efficiency and accuracy.
| Mualliflar | Назаров, Ф., Салимова, М., Шукуров, Б. |
|---|---|
| Jurnal | Рақамли технологияларнинг назарий ва амалий масалалари |
| Nashr sanasi | 2026-05-15 |
| Jild | 9 |
| Son | 2 |
| Betlar | 54-63 |
| Til | Ingliz |
| DOI | 10.62132/ijdt.v9i2.376 |
DOI: 10.62132/ijdt.v9i2.376 · Maqolaning asl sahifasi
WQI, сенсорные технологии, искусственный интеллект, машинное обучение, decision tree, random forest, SVM, min-max scaling, алгоритм SMOTE, WQI, sensor technology, artificial intelligence, machine learning, decision tree, random forest, SVM, min-max scaling, SMOTE algorithm
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