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<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>Water and Wastewater Consulting Engineers</PublisherName>
				<JournalTitle>Journal of Water and Wastewater; Ab va Fazilab (in persian)</JournalTitle>
				<Issn>1024-5936</Issn>
				<Volume>18</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2007</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>River Stream-Flow and Zayanderoud Reservoir Operation Modeling Using the Fuzzy Inference System</ArticleTitle>
<VernacularTitle>River Stream-Flow and Zayanderoud Reservoir Operation Modeling Using the Fuzzy Inference System</VernacularTitle>
			<FirstPage>25</FirstPage>
			<LastPage>34</LastPage>
			<ELocationID EIdType="pii">2157</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Saeed</FirstName>
					<LastName>Jamali</LastName>
<Affiliation>PhD Student, Department of Civil Engineering, Sharif University of Technology</Affiliation>

</Author>
<Author>
					<FirstName>Ahmad</FirstName>
					<LastName>Abrishamchi</LastName>
<Affiliation>Professor, Department of Civil Engineering, Sharif University of Technology</Affiliation>

</Author>
<Author>
					<FirstName>Massoud</FirstName>
					<LastName>Tajrishy</LastName>
<Affiliation>Associate Professor, Department of Civil Engineering, Sharif University of Technology</Affiliation>
<Identifier Source="ORCID">0000-0001-9252-8213</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2006</Year>
					<Month>03</Month>
					<Day>09</Day>
				</PubDate>
			</History>
		<Abstract>The Zayanderoud basin is located in the central plateau of Iran. As a result of population increase and agricultural and industrial developments, water demand on this basin has increased extensively. Given the importance of reservoir operation in water resource and management studies, the performance of fuzzy inference system (FIS) for Zayanderoud reservoir operation is investigated in this paper. The model of operation consists of two parts. In the first part, the seasonal river stream-flow is forecasted using the fuzzy rule-based system. The southern oscillated index, rain, snow, and discharge are inputs of the model and the seasonal river stream-flow its output. In the second part, the operation model is constructed. The amount of releases is first optimized by a nonlinear optimization model and then the rule curves are extracted using the fuzzy inference system. This model operates on an &quot;if-then&quot; principle, where the &quot;if&quot; is a vector of fuzzy permits and &quot;then&quot; is the fuzzy result. The   reservoir storage capacity, inflow, demand, and year condition factor are used as permits. Monthly release is taken as the consequence. The Zayanderoud basin is investigated as a case study. Different performance indices such as reliability, resiliency, and vulnerability are calculated. According to results, FIS works more effectively than the traditional reservoir operation methods such as standard operation policy (SOP) or linear regression.</Abstract>
			<OtherAbstract Language="FA">The Zayanderoud basin is located in the central plateau of Iran. As a result of population increase and agricultural and industrial developments, water demand on this basin has increased extensively. Given the importance of reservoir operation in water resource and management studies, the performance of fuzzy inference system (FIS) for Zayanderoud reservoir operation is investigated in this paper. The model of operation consists of two parts. In the first part, the seasonal river stream-flow is forecasted using the fuzzy rule-based system. The southern oscillated index, rain, snow, and discharge are inputs of the model and the seasonal river stream-flow its output. In the second part, the operation model is constructed. The amount of releases is first optimized by a nonlinear optimization model and then the rule curves are extracted using the fuzzy inference system. This model operates on an &quot;if-then&quot; principle, where the &quot;if&quot; is a vector of fuzzy permits and &quot;then&quot; is the fuzzy result. The   reservoir storage capacity, inflow, demand, and year condition factor are used as permits. Monthly release is taken as the consequence. The Zayanderoud basin is investigated as a case study. Different performance indices such as reliability, resiliency, and vulnerability are calculated. According to results, FIS works more effectively than the traditional reservoir operation methods such as standard operation policy (SOP) or linear regression.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Fuzzy inference system</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Reservoir operation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Performance Indices</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Southern Oscillated Index</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Standard Operation Policy</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">linear regression</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.wwjournal.ir/article_2157_d542599794c1cf067d90638b5d3911f3.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
