Neutrosophic Bicubic B-spline Surface Interpolation Model for Uncertainty Data

Dealing with the uncertainty data problem using neutrosophic data is difficult since certain data are wasted due to noise. To address this issue, this work proposes a neutrosophic set (NS) strategy for interpolating the B-spline surface. The purpose of this study is to visualize the neutrosophic bicubic B-spline surface (NBB-sS) interpolation model. Thus, the principal results of this study introduce the NBB-sS interpolation method for neutrosophic data based on the NS notion. The neutrosophic control net relation (NCNR) is specified first using the NS notion. The B-spline basis function is then coupled to the NCNR to produce the NBB-sS. This surface is then displayed using an interpolation method that comprises surfaces representing truth, indeterminacy, and false membership. There is a numerical example for constructing the NBB-sS using interpolation and will use quantitative data in the form of discrete numerical cases, particularly in neutrosophic numbers. The major conclusion of this study is a mathematical representation of NBB-sS by using the interpolation method was introduced and visualized for a neutrosophic data problem. The scientific value contributed to this study is an acceptance of uncertainty. Therefore, since it incorporates geometric modeling, this work can make a significant contribution to the neutrosophic decision model.