This article explores the development of algorithmic and software support for smart irrigation systems aimed at efficient use of water resources in horticulture. A comparative analysis of traditional and modern irrigation methods is presented. The main focus is on calculating evapotranspiration using the Penman–Monteith method and predicting soil moisture through Machine Learning (ML) algorithms, particularly the Random Forest method. The article includes Python code fragments that illustrate the system’s operational logic.
| Mualliflar | Pirimov, Odil Jo‘rayevich, Nasriddinov, Azizbek G‘ofir o‘g‘li, Pirimov, Odil Jo‘rayevich, Nasriddinov, Azizbek G‘ofir o‘g‘li, Pirimov, Odil Jo‘rayevich, Nasriddinov, Azizbek G‘ofir o‘g‘li |
|---|---|
| Jurnal | Agro ILM |
| Nashr sanasi | 2025-12-29 |
| Jild | 120 |
| Son | 9 |
| Betlar | 156-157 |
| Til | O‘zbek |
Aqlli qishloq xo‘jaligi, IoT, evapotranspiratsiya, mashinali o‘qitish, Random Forest, mikrokontrollerlar, suvni tejash, умное сельское хозяйство, IoT, эвтранспирация, машинное обучение, Random Forest, микроконтроллеры, водосбережение, smart agriculture, IoT, evapotranspiration, machine learning, Random Forest, microcontrollers, water saving
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