Addressing the challenges of ambiguity in veterinary medicine, this study proposes a novel approach to cattle disease diagnosis using neutrosophic sets and the Sugeno fuzzy model. The research develops specialized algorithms designed to process the inconsistent and fuzzy datasets typical of animal diagnostics. The goal is to provide a high-precision diagnostic engine that adapts effectively to the unique characteristics of various bovine pathologies. The anticipated results provide a foundation for an automated early-warning system, significantly increasing the efficiency of veterinary interventions and the overall productivity of the livestock sector.
| Mualliflar | L. (Lola) Safarova, Z. Qudratova |
|---|---|
| Jurnal | Samarqand davlat universiteti ilmiy tadqiqotlar axborotnomasi |
| Nashr sanasi | 2026-07-01 |
| Jild | 1 |
| Son | 3 |
| Betlar | 50-55 |
| DOI | 10.59251/2181-3973.2025.v1.138.1.3887 |
DOI: 10.59251/2181-3973.2025.v1.138.1.3887 · Maqolaning asl sahifasi
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