Yazar "Fernandez-Gamiz, U." seçeneğine göre listele

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    An application of artificial neural networks for solving fractional higher-order linear integro-differential equations
    (Springer, 2023) Allahviranloo, T.; Jafarian, A.; Saneifard, R.; Ghalami, N.; Nia, S. Measoomy; Kiani, F.; Fernandez-Gamiz, U.
    This ongoing work is vehemently dedicated to the investigation of a class of ordinary linear Volterra type integro-differential equations with fractional order in numerical mode. By replacing the unknown function by an appropriate multilayered feed-forward type neural structure, the fractional problem of such initial value is changed into a course of non-linear minimization equations, to some extent. Put differently, interest was sparked in structuring an optimized iterative first-order algorithm to estimate solutions for the origin fractional problem. On top of that, some computer simulation models exemplify the preciseness and well-functioning of the indicated iterative technique. The outstanding accomplished numerical outcomes conveniently reflect the productivity and competency of artificial neural network methods compared to customary approaches.
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    The Investigation of Some Essential Concepts of Extended Fuzzy-Valued Convex Functions and Their Applications
    (Hindawi Ltd, 2024) Allahviranloo, T.; Shahryari, M. R. Balooch; Sedaghatfar, O.; Shahriari, M. R.; Saadati, R.; Noeiaghdam, S.; Fernandez-Gamiz, U.
    In this paper, we are thus motivated to define and introduce the extended fuzzy-valued convex functions that can take the singleton fuzzy values -infinity similar to and +infinity similar to at some points. Such functions can be characterized using the notions of effective domain and epigraph. In this way, we study important concepts such as fuzzy indicator function and fuzzy infimal convolution for extended fuzzy-valued functions. Finally, we introduce the concept of directional generalized derivative for extended above functions and its properties. Eventually, we give a practical example that will illustrate well the directional g-derivative for the extended fuzzy-valued convex function.