A new types of spline modeling using fuzzy linguistic approach AIP Conference Proceedings 1750, 020020 (2016) Abstract. The solution of a problem that involves uncertainty data that is characterized by complex process in which the phenomenon of incomplete information obtained is difficult to handle. Various mathematical models have been developed to handle problems involving uncertainty data. This paper introduced new concept of geometric modeling with intuitionistic fuzzy called intuitionistic fuzzy Bezier model. This model is constructed through intuitionistic fuzzy set theory and based on intuitionistic fuzzy number and intuitionistic fuzzy relation. A new control point namely intuitionistic fuzzy control point is defined. Next, the new control point is blended with the spline basis function to developed intuitionistic fuzzy Bezier model and the curve is shaped.

Abstract. The problem of fuzzy linguistic data is difficult to analyze. By the existing approaches are not be able to describe the data in the form of a generic figure which smooth and continuous. This is because the generalization of the problems of linguistic data in the form of curves and surfaces require a new of the models which characterized by a fuzzy linguistic. In this paper introduces new types of fuzzy spline models such as Fuzzy Linguistic Bezier and Fuzzy Linguistic B-Splines by using the definition of fuzzy linguistic control points. For the effectives of the model, some numerical examples are given at the end of this paper.

The control point is the most important element in the production of spline curve or surface model. This is because any changes of control points in the spline model affect the shape of the resulting curve or surface. Wahab and colleagues have introduced fuzzy control points to solve the problem of uncertainty prevailing in the spline modeling. However, based on this concept, this paper will discusses a new type of fuzzy control point that can generates a spline space curve model in 3-dimensional. This is because the generated control point is a 3-dimensional that satisfies the basic concepts of fuzzy set was introduced by Zadeh. However, this paper only taking a B-Spline model as a numerical example in the discussed model.

Fuzzy Linguistic is an extension of fuzzy set theory was introduced by Zadeh. Normally fuzzy linguistic is often associated with linguistic variables generated by a function modifier is also known as a hedges. This paper discusses the theorems and definitions of fuzzy linguistic perspective geometric modeling to produce Fuzzy Linguistic Control Point (FLCP). Fuzzy Linguistic Control Points have been blended in with the spline basic functions of the model to produce a few splines’s model are characterized by fuzzy linguistics. At the end of this article will discuss some numerical examples of Fuzzy Linguistic Bezier Model.