A novel computational approach to approximate fuzzy interpolation polynomials

This paper build a structure of fuzzy neural network, which is well sufficient to gain a fuzzy interpolation polynomial of the form yp=anxnp+⋯+a1xp+a0 where aj is crisp number (for j=0,…,n), which interpolates the fuzzy data (xj,yj)(forj=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