This research aims to develop improved methods for diagnosing diseases in cattle using the principles of neutrosophic sets and Sugeno fuzzy inference. The study proposed new algorithms and models that effectively process fuzzy and uncertain information characteristic of veterinary diagnostics. The main goal of the work is to create a diagnostic system with high accuracy and adaptability to various conditions and specific cases of diseases. The expected outcome is the development of an effective tool for early detection of diseases in cattle, which will significantly increase the efficiency of veterinary practice and improve animal welfare.
| Mualliflar | Сафарова, Лола |
|---|---|
| Jurnal | Рақамли технологияларнинг назарий ва амалий масалалари |
| Nashr sanasi | 2024-10-09 |
| Jild | 7 |
| Son | 3 |
| Betlar | 61-67 |
| Til | Rus |
| DOI | 10.62132/ijdt.v7i3.197 |
DOI: 10.62132/ijdt.v7i3.197 · Maqolaning asl sahifasi
Диагностика заболеваний крупного рогатого скота, нейтрософские множества, нечеткий вывод Сугено, ветеринарная диагностика, нечеткая и неопределенная информация, диагностическая система, Diagnosis of cattle diseases, neutrosophic sets, fuzzy sugeno inference, veterinary diagnostics, fuzzy and uncertain information, diagnostic system
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