Matematik Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/413

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Author: search.filters.author.Al Qurashi, Maysaa MohamedPublisher: search.filters.publisher.Springer international Publishing Ag

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  • Article
    Citation - WoS: 10
    Citation - Scopus: 15
    A Novel Computational Approach To Approximate Fuzzy Interpolation Polynomials
    (Springer international Publishing Ag, 2016) Jafari, Raheleh; Al Qurashi, Maysaa Mohamed; Baleanu, Dumitru; Jafarian, Ahmad; Mohamed Al Qurashi, Maysaa
    This 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.