Modeling of an Interval Type-2 Neutrosophic Bézier Surface by Using Interpolation Method

Abstract

A generalization of the type-1 neutrosophic set, interval type-2 fuzzy set, and intuitionistic fuzzy set is the interval type-2 neutrosophic set (IT2NS).  This study will show how to use the interpolation approach to visualize the interval type-2 neutrosophic Bézier surface (IT2NBS) model. However, the existence of truth, indeterminacy, and falsity membership functions in neutrosophic features makes the model challenging to visualize. Apart from that, the attributes of IT2NS have an upper and lower bound, which makes it difficult. Using the IT2NS theory, this study will first introduce an interval type-2 neutrosophic control net relation (IT2NCNR) to build the model. The IT2NBS models will be represented by blending the IT2NCNR and the Bernstein basis function. Afterward, the truth, indeterminacy, and falsity memberships of the IT2NCNR are interpolated for both the upper and lower bounds to show the IT2NBSs. A review of the algorithm used to create the IT2NBS interpolation models will wrap up the study. Fortunately, the results of this study will yield a predictive model that is used in many medical applications, such as picture blurring detection, and cancer level prediction.