Nonlinear Interpolation in Hedge Algebras Associating Genetic Algorithm to Solve the Bell-Shaped Function Approximation Problems
Nguyen Tien Duy1, Nghiem Van Tinh2, Nguyen Tuan Anh3

1M.Sc Nguyen Tien Duy, Department of Electronic Engineering Technology, Thainguyen University, Vietnam.
2Nghiem Van Tinh, M.Sc, Department of Electronic Engineering Technology, Thainguyen University, Vietnam.
3Nguyen Tuan Anh, M.Sc, Department of Information and Communication Technology, Thainguyen University, Vietnam.
Manuscript received on 14 June 2015 | Revised Manuscript received on 23 June 2015 | Manuscript Published on 30 June 2015 | PP: 16-20 | Volume-5 Issue-1, June 2015 | Retrieval Number: L20500541215/15©BEIESP
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Abstract: Recently, there have been many works published related to approximation ability of the function using fuzzy logic and hedge algebras. These results showed that the approximation has a large error. In this paper, we propose a new method in improving the approximation accuracy of the function using hedge algebra by executing the normalization and denormalization by nonlinear interpolation. Moreover, we apply genetic algorithm to optimize the algorithms of hedge algebra. The function we choose to be approximate is the bell-shaped function. It is proved in the result that approximation bell surface has a significant decrease compared with the last results. Therefore, the effectiveness of hedge algebra in solving the approximation problems using algorithm can be revealed; as a result, it is advisable that nonlinear interpolation in hedge algebra to these problems such as nonlinear function approximation, fuzzy control be used.
Keywords: Approximation Inference, Identification, Function Approximation, Hedge Algebras.

Scope of the Article: Algorithm Engineering