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<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Kashan</PublisherName>
				<JournalTitle>Mathematics Interdisciplinary Research</JournalTitle>
				<Issn>2538-3639</Issn>
				<Volume>10</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2025</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Approximation‎ ‎of a Leading‎ ‎Coefficient in an Inverse Heat Conduction Problem via the Ritz Method</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>159</FirstPage>
			<LastPage>182</LastPage>
			<ELocationID EIdType="pii">114910</ELocationID>
			
<ELocationID EIdType="doi">10.22052/mir.2025.256068.1492</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Maryam</FirstName>
					<LastName>Ghorbani</LastName>
<Affiliation>‎Department of Mathematics,
         ‎University of Scince and Technology of Mazandaran,
        ‎Behshahr‎, ‎Iran</Affiliation>

</Author>
<Author>
					<FirstName>Kamal</FirstName>
					<LastName>Rashedi</LastName>
<Affiliation>‎Department of Mathematics,
         ‎University of Scince and Technology of Mazandaran,
        ‎Behshahr‎, ‎Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2024</Year>
					<Month>12</Month>
					<Day>28</Day>
				</PubDate>
			</History>
		<Abstract>‎This paper presents a numerical approach for reconstructing the leading coefficient in an inverse heat conduction problem (IHCP)‎. ‎We consider a one-dimensional heat equation with known input data‎, ‎including the initial condition‎, ‎a supplementary temperature measurement at the final time‎, ‎and two integral observations‎. ‎By incorporating the terminal condition‎, ‎the unknown spatially dependent coefficient is eliminated‎, ‎reducing the problem to a nonclassical parabolic equation‎. ‎The unknown temperature distribution and its derivatives are approximated and applied to the modified governing equation‎, ‎which is then discretized using operational matrices of differentiation‎. ‎To ensure stable derivative estimation‎, ‎the method is coupled with a regularization technique‎. ‎A least squares scheme is employed to formulate a nonlinear system of algebraic equations‎, ‎which is solved using Newton’s method‎. ‎The reliability of the proposed solution is demonstrated through several numerical examples‎.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Least squares technique‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Inverse heat equation‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Leading coefficient</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mir.kashanu.ac.ir/article_114910_55ba5850d43fcadb991c9eaeb8ad7d2b.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
