This paper makes a virus detection study based on the D-S theory of evidence,
which applies to two types of classifiers, support vector machines and probabilistic neural
networks to detect the virus. Then, the D-S theory of evidence is used to combine the
contribution of each individual classifier to obtain the final decision. The experiment tests and
result analyses demonstrate that it is efficient for unknown viruses and variant viruses to
improve accuracy rate of integration virus detector by using D-S theory to create the isomeric
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Copyright (c) 2022 *Abdumuminov Abdurafiq Abdurashidovich, Ibragimov Jalaliddin Obidjon o'g'li, Shoraimov Khusanboy Uktamboyevich