<?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 Tabriz</PublisherName>
				<JournalTitle>Journal of Geography and Planning</JournalTitle>
				<Issn>2008-8078</Issn>
				<Volume></Volume>
				<Issue>Articles in Press</Issue>
				<PubDate PubStatus="epublish">
					<Year>2025</Year>
					<Month>10</Month>
					<Day>07</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Analysis of urban resilience using the combination of fuzzy model and learning machine, a case study of Tabriz city</ArticleTitle>
<VernacularTitle>Analysis of urban resilience using the combination of fuzzy model and learning machine, a case study of Tabriz city</VernacularTitle>
			<FirstPage></FirstPage>
			<LastPage></LastPage>
			<ELocationID EIdType="pii">20527</ELocationID>
			
<ELocationID EIdType="doi">10.22034/gp.2025.63290.3339</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Reza</FirstName>
					<LastName>Mahmodnezhad</LastName>
<Affiliation>karmand</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2024</Year>
					<Month>12</Month>
					<Day>24</Day>
				</PubDate>
			</History>
		<Abstract>In recent years, the vulnerability of Iran&amp;#039;s big cities has increased against unexpected incidents and accidents, and in contrast to the low level of resilience, human life has been endangered in these cities. Based on this, the aim of this article is to analyze urban resilience using a combination of fuzzy model and machine learning in Tabriz city as a metropolis in the northwestern region of the country. This research is applied-developmental in terms of purpose, descriptive-analytical in terms of method. which are three physical, social and natural components with 41 effective indicators in urban resilience, which were compiled and compiled based on questioning and examining various sources. Then, preparing the maps of each variable and creating fuzzy layers using the fuzzy neural network model in the Idris Terrset software environment, the resilience of Tabriz city was determined. Validation with the help of ROC curve is equal to 0.856, which shows a very good result. According to the obtained results, About 10 percent of the area of Tabriz city is in dangerous conditions in terms of resilience, while 36 percent of the total city area has a high level of flexibility. Ultimately, separate recommendations were presented based on the resilience conditions and land uses.&lt;br /&gt;
Key words: urban resilience - fuzzy model - learning machine - Tabriz</Abstract>
			<OtherAbstract Language="FA">In recent years, the vulnerability of Iran&amp;#039;s big cities has increased against unexpected incidents and accidents, and in contrast to the low level of resilience, human life has been endangered in these cities. Based on this, the aim of this article is to analyze urban resilience using a combination of fuzzy model and machine learning in Tabriz city as a metropolis in the northwestern region of the country. This research is applied-developmental in terms of purpose, descriptive-analytical in terms of method. which are three physical, social and natural components with 41 effective indicators in urban resilience, which were compiled and compiled based on questioning and examining various sources. Then, preparing the maps of each variable and creating fuzzy layers using the fuzzy neural network model in the Idris Terrset software environment, the resilience of Tabriz city was determined. Validation with the help of ROC curve is equal to 0.856, which shows a very good result. According to the obtained results, About 10 percent of the area of Tabriz city is in dangerous conditions in terms of resilience, while 36 percent of the total city area has a high level of flexibility. Ultimately, separate recommendations were presented based on the resilience conditions and land uses.&lt;br /&gt;
Key words: urban resilience - fuzzy model - learning machine - Tabriz</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">urban Resilience</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fuzzy model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">learning machine</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Tabriz</Param>
			</Object>
		</ObjectList>
</Article>
</ArticleSet>
