Application of Interval Neutrosophic Logic Model for Diagnosis of Cattle Disease

In this paper, we propose a method of interval neutrosophic logic for solving the urgent problem of diagnosing cattle diseases under conditions of data uncertainty. Based on the theory of interval neutrosophic sets, an algorithm has been developed that takes into account the degree of likelihood, falsity, and uncertainty, which ensures more accurate modeling and analysis. The main result of the study is the construction of an interval neutrosophic Sugeno model designed to diagnose cattle diseases such as osteodystrophy, ketosis, and hypomicroelementosis. The model demonstrates high efficiency: the diagnostic accuracy reached 92%, which exceeds the results of other methods, including classical Sugeno models and statistical approaches. A comparative analysis of the developed model with alternative methods was carried out, confirming its advantages under conditions of uncertainty and data heterogeneity. The proposed method has the potential for application in veterinary practice, especially in conditions of limited resources, where high diagnostic accuracy and reliability are required.