A novel computational approach to approximate fuzzy interpolation polynomials

摘要

This paper build a structure of fuzzy neural network, which is well sufficient to gain a fuzzy interpolation polynomial of the form yp=anxpn+⋯+a1xp+a0 where aj is crisp number (for j = 0, …, n), which interpolates the fuzzy data (xj, yj) (for j = 0, …, n). Thus, a gradient descent algorithm is constructed to train the neural network in such a way that the unknown coefficients of fuzzy polynomial are estimated by the neural network. The numeral experimentations portray that the present interpolation methodology is reliable and efficient.