Jafarian, AhmadJafari, RahelehAl Qurashi, Maysaa MohamedBaleanu, Dumitru2020-04-172020-04-172016Jafarian, Ahmad...et al. (2016). "A novel computational approach to approximate fuzzy interpolation polynomials", Springerplus, Vol. 5.2193-1801http://hdl.handle.net/20.500.12416/3282This paper build a structure of fuzzy neural network, which is well sufficient to gain a fuzzy interpolation polynomial of the form y(p) = a(n)x(p)(n) +... + a(1)x(p) + a(0) where a(j) is crisp number (for j = 0,..., n), which interpolates the fuzzy data (x(j), y(j)) (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.eninfo:eu-repo/semantics/openAccessFuzzy Neural NetworksFuzzy Interpolation PolynomialCost FunctionLearning AlgorithmArticle510.1186/s40064-016-3077-5