Convex hull approach to fuzzy regression analysis and its application to oral age model

Fuzzy multivariate analyses including linear regression analysis, fuzzy time-series analysis, fuzzy possibilistic linear model, etc. are formulated in terms of the extension principle. One objective of a fuzzy linear regression model is to build a model using fuzzy which represent the possibilities included in the system. In this paper in order that we can overcome this issue, we propose the effective method to decrease drastically the number of samples in terms of convex hull method. In this paper stress is placed on that (1) only vertex points obtained by the convex hull are constraints on a linear programming on that (2) the convex hull approach works efficiently in real-time data gathering, and on that (3) the number of vertexes obtained by the convex hull will not increase so much. Using a numerical example, we show difference between both the convex hull and the conventional approaches to decrease the number of samples in building the model. We also illustrate and build the oral age model using real data about the age and the number of sound teeth based on Convex Hull.