A Dissimilarity relational bipolar operator in the analysis of obesity-induced illness

Fuzzy set theory and its extensions perform exceptionally well when managing ambiguous information. The bipolar fuzzy Set is one of the extensions that depict the positive and negative aspects of the data. In many fields, the bipolar fuzzy matrix effectively handles the data. In this artifact, we define a new dissimilarity relational operator of the bipolar fuzzy matrix. A novel algorithm is proposed using the new augmented operator. Additionally, we illustrate the suggested algorithm for identifying obesity-induced illness in the decision-making domain.