Modeling the propagation of fractional inequalities via generalized fractional operators with artificial neural networks

This paper examines the generalized reverse forms of well-known Minkowski, Hölder and Hermite-Hadamard (HH)-Fejér inequalities within an interval-valued (ι.υ) (⋋1q1+1,℧) class of convexity by deploying the generalized k-Prabhakar fractional integral operator (FIO). Our findings exhibit wide relevanc...

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Autori principali:	Ahsan Mehmood, Muhammad Younis, Muhammad Samraiz, Gauhar Rahman, Kamal Shah, Bahaaeldin Abdalla, Thabet Abdeljawad
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2026-05-01
Serie:	Ain Shams Engineering Journal
Soggetti:	Hermite-Hadamard-Fejér inequality Mittag–Leffler function Hölder’s inequality Generalized fractional integrals Artificial neural networks
Accesso online:	http://www.sciencedirect.com/science/article/pii/S209044792600122X
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