Hilfer fractional stochastic evolution equations on the positive semi-axis

The focus of this article lies in the existence of global mild solutions for Hilfer fractional stochastic evolution equations (HFSEEs) on the positive semi-axis (0,+∞) with a derivative order greater than 32 and less than 2. A significant challenge, which also presents novelty here, is to extend the...

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Published in:Alexandria Engineering Journal
Main Authors: Min Yang, Qingqing Huan, Haifang Cui, Qiru Wang
Format: Article
Language:English
Published: Elsevier 2024-10-01
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016824008536
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author Min Yang
Qingqing Huan
Haifang Cui
Qiru Wang
author_facet Min Yang
Qingqing Huan
Haifang Cui
Qiru Wang
author_sort Min Yang
collection DOAJ
container_title Alexandria Engineering Journal
description The focus of this article lies in the existence of global mild solutions for Hilfer fractional stochastic evolution equations (HFSEEs) on the positive semi-axis (0,+∞) with a derivative order greater than 32 and less than 2. A significant challenge, which also presents novelty here, is to extend the generalized Ascoli–Arzela (A–A) theorem established in Zhou and He (2022) to the stochastic case under the associated sine family {S(t)}t≥0 not necessary compact. Then, by relying on our newly established generalized A–A theorem, standard stochastic analysis theory and Schauder’s fixed point principle, we derive the existence of global mild solutions for the addressed system. Finally, we demonstrate the feasibility of our obtained results through an illustrative example.
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spelling doaj-art-e30be4b167034fbdbdda76de8de2cba42025-09-03T02:17:38ZengElsevierAlexandria Engineering Journal1110-01682024-10-0110438639510.1016/j.aej.2024.07.111Hilfer fractional stochastic evolution equations on the positive semi-axisMin Yang0Qingqing Huan1Haifang Cui2Qiru Wang3School of Mathematics, Taiyuan University of Technology, Taiyuan, 030024, China; Corresponding author.School of Mathematics, Taiyuan University of Technology, Taiyuan, 030024, ChinaSchool of Mathematics, Taiyuan University of Technology, Taiyuan, 030024, ChinaSchool of Mathematics, Sun Yat-sen University, Guangzhou, 510275, ChinaThe focus of this article lies in the existence of global mild solutions for Hilfer fractional stochastic evolution equations (HFSEEs) on the positive semi-axis (0,+∞) with a derivative order greater than 32 and less than 2. A significant challenge, which also presents novelty here, is to extend the generalized Ascoli–Arzela (A–A) theorem established in Zhou and He (2022) to the stochastic case under the associated sine family {S(t)}t≥0 not necessary compact. Then, by relying on our newly established generalized A–A theorem, standard stochastic analysis theory and Schauder’s fixed point principle, we derive the existence of global mild solutions for the addressed system. Finally, we demonstrate the feasibility of our obtained results through an illustrative example.http://www.sciencedirect.com/science/article/pii/S1110016824008536Hilfer fractional derivativeStochastic evolution equationsMild solutionsPositive semi-axis
spellingShingle Min Yang
Qingqing Huan
Haifang Cui
Qiru Wang
Hilfer fractional stochastic evolution equations on the positive semi-axis
Hilfer fractional derivative
Stochastic evolution equations
Mild solutions
Positive semi-axis
title Hilfer fractional stochastic evolution equations on the positive semi-axis
title_full Hilfer fractional stochastic evolution equations on the positive semi-axis
title_fullStr Hilfer fractional stochastic evolution equations on the positive semi-axis
title_full_unstemmed Hilfer fractional stochastic evolution equations on the positive semi-axis
title_short Hilfer fractional stochastic evolution equations on the positive semi-axis
title_sort hilfer fractional stochastic evolution equations on the positive semi axis
topic Hilfer fractional derivative
Stochastic evolution equations
Mild solutions
Positive semi-axis
url http://www.sciencedirect.com/science/article/pii/S1110016824008536
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