<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Sistan and Baluchestan</PublisherName>
				<JournalTitle>Iranian Journal of Fuzzy Systems</JournalTitle>
				<Issn>1735-0654</Issn>
				<Volume>20</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2023</Year>
					<Month>02</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Quintuple intuitionistic fuzzy implications reasoning algorithms and application</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>153</FirstPage>
			<LastPage>170</LastPage>
			<ELocationID EIdType="pii">7352</ELocationID>
			
<ELocationID EIdType="doi">10.22111/ijfs.2023.7352</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Z. S.</FirstName>
					<LastName>Liu</LastName>
<Affiliation>Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhoushan, 316022, China</Affiliation>

</Author>
<Author>
					<FirstName>X.</FirstName>
					<LastName>Li</LastName>
<Affiliation>School of Information and Engineering, Zhejiang Ocean University, Zhoushan, 316000, China</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2023</Year>
					<Month>01</Month>
					<Day>15</Day>
				</PubDate>
			</History>
		<Abstract>Atanassov&#039;s intuitionistic fuzzy sets have succussed in the application of decision making, data mining, artificial intelligence, image processing, and so on. In these applications, intuitionistic fuzzy reasoning plays a crucial role. To improve the quality of intuitionistic fuzzy reasoning, this paper presents a quintuple intuitionistic fuzzy implication principle (QIIP) to resolve intuitionistic fuzzy&lt;br /&gt;modus ponens (IFMP) and intuitionistic fuzzy modus tollens (IFMT) problems. The QIIP algorithms of IFMP and IFMT problems for intuitionistic R-implication, S-implication, and several fuzzy implications are represented. Moreover, we investigate the recovery property and continuity of QIIP algorithms for IFMP and IFMT.&lt;br /&gt;Finally, an application example for medical diagnosis is implemented to illustrate our proposed approaches.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Intuitionistic fuzzy set</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">intuitionistic fuzzy implications</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fuzzy reasoning</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">recovery property</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Continuity</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ijfs.usb.ac.ir/article_7352_b5ff1fab5a1f65f978d1416c52077a0b.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
