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<Article>
<Journal>
				<PublisherName>Azarbaijan Shahid Madani University</PublisherName>
				<JournalTitle>Communications in Combinatorics and Optimization</JournalTitle>
				<Issn>2538-2128</Issn>
				<Volume>11</Volume>
				<Issue>3</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>09</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>On Hermite-Hadamard Type Inequalities in Stochastic Fractional Calculus</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>1059</FirstPage>
			<LastPage>1071</LastPage>
			<ELocationID EIdType="pii">15076</ELocationID>
			
<ELocationID EIdType="doi">10.22049/cco.2025.30980.2689</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Asraa</FirstName>
					<LastName>Najm Abood</LastName>
<Affiliation>Department of Mathematics, College of Dentistry, Diyala University, Diyala, Iraq</Affiliation>

</Author>
<Author>
					<FirstName>Rawaa Khalil</FirstName>
					<LastName>Ibrahim</LastName>
<Affiliation>Department of Mathematics, College of Dentistry, University of Diyala, Diyala, Iraq</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>09</Month>
					<Day>08</Day>
				</PubDate>
			</History>
		<Abstract>This paper extends Hermite-Hadamard type inequalities within the framework of stochastic fractional calculus. We investigate how fractional integrals, which account for memory effects, interact with random processes. Our work presents three main contributions. First, we provide an error bound for approximating a standard integral of a smooth, deterministic function using stochastic fractional integrals. Second, we extend the well-known Hermite-Hadamard inequality, which applies to convex functions, to the setting of convex stochastic processes, showing how their expected values are bounded by these integrals. Finally, we derive specific mean-square error bounds when approximating a standard Brownian motion using its stochastic fractional integrals. These results enhance our understanding of stochastic fractional inequalities, offering new tools for analyzing complex systems influenced by both memory and randomness.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Fractional calculus</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Stochastic calculus</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Hermite-Hadamard inequality</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Riemann- Liouville fractional integral</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://comb-opt.azaruniv.ac.ir/article_15076_d59e0a6111c47b0ff2c87c9134bf06e0.pdf</ArchiveCopySource>
</Article>
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