Bézier Curve Interpolation Model for Complex Data by Using Neutrosophic Approach

Since certain data are ignored owing to noise, coping with the complex data with neutrosophic features is problematic. This paper suggests a neutrosophic set strategy for interpolating the Bézier curve to overcome this issue. Thus, depending on the neutrosophic set notion, this work introduces the Bézier curve interpolation method for neutrosophic data. Using the neutrosophic set and its attributes, the neutrosophic control point is specified first. After that, the Bernstein basis function is linked to the control point and yields a neutrosophic Bézier. This curve is then shown using an interpolation approach that includes curves indicating membership, indeterminacy, and non-membership. Before the conclusion of this article, there is a numeric example and an algorithm for developing the neutrosophic Bézier curve using interpolation. Based on the results obtained, the neutrosophic set can deal with the complex data by treating all data including the uncertainty data as indeterminacy membership functions. In conclusion, this model can be used for real applications involving big data analysis.