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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Payame Noor University (PNU)</PublisherName>
				<JournalTitle>Control and Optimization in Applied Mathematics</JournalTitle>
				<Issn>2383-3130</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>10</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Control Parametrization Enhancing Technique for Multi-Objective Optimal Control of HIV Dynamic</ArticleTitle>
<VernacularTitle>کنترل بهینه چندهدفه دینامیک ‎HIV‎ به کمک تکنیک پارامتری کردن کنترل</VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>21</LastPage>
			<ELocationID EIdType="pii">3392</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Hassan</FirstName>
					<LastName>Zarei</LastName>
<Affiliation>Department of Mathematic, Payame Noor University, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>06</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>In this paper‎, ‎a computational approach is adopted for solving a multi-objective optimal control problem (MOOCP) formulation of optimal drug scheduling in human immunodeficiency (HIV) virus infected by individuals‎. ‎The MOOCP‎, ‎which uses a mathematical model of HIV infection‎, ‎has some incompatible objectives‎. ‎The objectives are maximizing the survival time of patients‎, ‎the level of D4‎+ ‎T-cells and the level of cytotoxic T-lymphocytes (CTLs)‎, ‎and minimizing the viral load and the drug costs‎. ‎In this approach the fuzzy goals described by the linear membership functions‎, ‎are incorporated for the objectives and the optimal solution is investigated by maximizing the degree of attainment of the aggregated fuzzy goals resulting a fuzzy goal optimal control problem (FGOCP)‎. ‎Using the minimum operator for aggregation of fuzzy goals‎, ‎the FGOCP is converted into a constrained optimal control problem (OCP) in canonical form‎. ‎The control parametrization enhancing technique (CPET) is used for approximating the OCP by an optimal parameter selection problem‎, ‎with the final goal of implementing continuous and interrupted (structured treatment interruptions‎, ‎STI) combinations of reverse transcriptase inhibitor (RTI) and protease inhibitor (PI) drug efficacies‎. ‎Efficiency of the proposed method is confirmed by numerical simulations.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Multi-objective problem‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Optimal control‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Fuzzy goal programming‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Therapy optimization</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mathco.journals.pnu.ac.ir/article_3392_b126b5fd552ee258e1bd281c8a5dc268.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Payame Noor University (PNU)</PublisherName>
				<JournalTitle>Control and Optimization in Applied Mathematics</JournalTitle>
				<Issn>2383-3130</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Numerical Solution of Optimal Heating of Temperature Field in Uncertain Environment Modelled by the use of Boundary Control</ArticleTitle>
<VernacularTitle>حل عددی گرمادهی بهینه میدان دمایی در محیط تصادفی مدل‌سازی شده با استفاده از کنترل مرزی</VernacularTitle>
			<FirstPage>23</FirstPage>
			<LastPage>38</LastPage>
			<ELocationID EIdType="pii">3395</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Nehrani</LastName>
<Affiliation>faculty of mathematical sciences, university of guilan, rasht, iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Keyanpour</LastName>
<Affiliation>Faculty of mathematical sciences, University of Guilan, Rasht, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>01</Month>
					<Day>12</Day>
				</PubDate>
			</History>
		<Abstract>‎In the present paper‎, ‎optimal heating of temperature field which is modelled as a boundary optimal control problem‎, ‎is investigated in the uncertain environments and then it is solved numerically‎. ‎In physical modelling‎, ‎a partial differential equation with stochastic input and stochastic parameter are applied as the constraint of the optimal control problem‎. ‎Controls are implemented as Dirichlet boundary conditions and representing the heating elements on the boundary of the field‎. ‎In numerical quantification‎, ‎stochastic input and parameter are approximated via Karhunen-Lo\&#039;eve expansion and inserted to the problem‎. ‎In fact‎, ‎for numerical discretization of the problem stochastic Galerkin method is applied to generalize polynomial chaos‎. ‎Numerical optimization is performed via gradient method‎. ‎The problem is fully implemented and in order to show the applicability of the method‎, ‎numerical examples are solved and numerical results are represented through figures.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Boundary optimal control‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Stochastic partial differential equation‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Stochastic quantification‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Gradient method</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mathco.journals.pnu.ac.ir/article_3395_2c4e86ec7879dc9ee757e6be0008d18b.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Payame Noor University (PNU)</PublisherName>
				<JournalTitle>Control and Optimization in Applied Mathematics</JournalTitle>
				<Issn>2383-3130</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>09</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Robust Control Synchronization on Multi-Story Structure under Earthquake Loads and Random Forces using H∞ Algorithm</ArticleTitle>
<VernacularTitle>هماهنگ‌سازی الگوریتم کنترل مقاوم H∞‎ برای سازه‌های چند طبقه تحت بار زلزله و نیروهای تصادفی</VernacularTitle>
			<FirstPage>39</FirstPage>
			<LastPage>52</LastPage>
			<ELocationID EIdType="pii">3397</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Javad</FirstName>
					<LastName>Mesbahi</LastName>
<Affiliation>PNU, Applied Mathematics Department</Affiliation>

</Author>
<Author>
					<FirstName>Alaeddin</FirstName>
					<LastName>Malek</LastName>
<Affiliation>Applied Mathematics Dept. Tarbiat Modares University
Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Behnoush</FirstName>
					<LastName>Salimbahrami</LastName>
<Affiliation>Civil Eng Dept. PayameNoor University</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>12</Month>
					<Day>14</Day>
				</PubDate>
			</History>
		<Abstract>In this paper‎, ‎the concept of synchronization control along with robust H∞ control are considered to evaluate the seismic response control on multi-story structures‎. ‎To show the accuracy of the novel algorithm‎, ‎a five-story structure is evaluated under the EL-Centro earthquake load‎. ‎In order to find the performance of the novel algorithm‎, ‎random and uncertainty processes corresponding to Riccati equation is solved under a specific dynamic‎. ‎Time history graphs corresponding to maximum displacement and floors force control are presented and evaluated‎. ‎Despite the existence of random process and uncertainty in structure‎, ‎stability and optimal performances are shown.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Synchronization‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Random process and uncertainty‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Robust H∞ control‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎EL-Centro earthquake load‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Riccati equation</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mathco.journals.pnu.ac.ir/article_3397_ac7064440ef6ea12174108d5882a4940.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Payame Noor University (PNU)</PublisherName>
				<JournalTitle>Control and Optimization in Applied Mathematics</JournalTitle>
				<Issn>2383-3130</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Solving System of Nonlinear Equations by using a New Three-Step Method</ArticleTitle>
<VernacularTitle>حل دستگاه معادلات غیرخطی با استفاده از یک روش سه گامی جدید</VernacularTitle>
			<FirstPage>53</FirstPage>
			<LastPage>62</LastPage>
			<ELocationID EIdType="pii">3398</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mehdi</FirstName>
					<LastName>Ahmadi</LastName>
<Affiliation>Department of Mathematics, Malayer University, Malayer, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Hamid</FirstName>
					<LastName>Esmaeili</LastName>
<Affiliation>Department of Mathematics, Bu-Ali Sina University, Hamedan, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>R</FirstName>
					<LastName>Erfanifar</LastName>
<Affiliation>Department of Mathematics, Bu-Ali Sina University, Hamedan, Iran.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>11</Month>
					<Day>13</Day>
				</PubDate>
			</History>
		<Abstract>In this paper‎, ‎we suggest a fifth order convergence three-step method for solving system of nonlinear equations‎. ‎Each iteration of the method requires two function evaluations‎, ‎two first Fr\&#039;{e}chet derivative evaluations and two matrix inversions‎. ‎Hence‎, ‎the efficiency index is $5^{1/({2n+4n^{2}+\frac{4}{3}n^{3}})}$‎, ‎which is better than that of other three-step methods‎. ‎The advantages of the method lie in the feature that this technique not only achieves an approximate solution with high accuracy‎, ‎but also improves the calculation speed‎. ‎Also‎, ‎under several mild conditions the convergence analysis of the proposed method is provided‎. ‎An efficient error estimation is presented for the approximate solution‎. ‎Numerical examples are included to demonstrate the validity and applicability of the method and the comparisons are made with the existing results.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Nonlinear equations‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Iterative method‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Convergence order‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Efficiency index</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mathco.journals.pnu.ac.ir/article_3398_cee896e67e39e179b12bcb4a52ca7cc3.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Payame Noor University (PNU)</PublisherName>
				<JournalTitle>Control and Optimization in Applied Mathematics</JournalTitle>
				<Issn>2383-3130</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Comparative Analysis of Machine Learning Algorithms with Optimization Purposes</ArticleTitle>
<VernacularTitle>تحلیل تطبیقی الگوریتم‌های یادگیری ماشین با اهداف بهینه‌سازی</VernacularTitle>
			<FirstPage>63</FirstPage>
			<LastPage>75</LastPage>
			<ELocationID EIdType="pii">3399</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Rohollah</FirstName>
					<LastName>Alesheykh</LastName>
<Affiliation>Payame Noor University</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>02</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		<Abstract>The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches‎. ‎Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data‎. ‎In this paper‎, ‎a methodology has been employed to optimize the precision of defect detection of concrete slabs depending on their qualitative evaluation‎. ‎Based on this idea‎, ‎some machine learning algorithms such as C4.5 decision tree‎, ‎RIPPER rule learning method and Bayesian network have been studied to explore the defect of concrete and to supply a decision system to speed up the defect detection process‎. ‎The results from the examinations show that the proposed RIPPER rule learning algorithm in combination with Fourier Transform feature extraction method could get a defect detection rate of 93% as compared to other machine learning algorithms.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">decision tree</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Bayesian network</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">rule learning algorithm</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Optimization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Soft Computing</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mathco.journals.pnu.ac.ir/article_3399_eac798a614b48609ebe90618f6dd2bca.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Payame Noor University (PNU)</PublisherName>
				<JournalTitle>Control and Optimization in Applied Mathematics</JournalTitle>
				<Issn>2383-3130</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>09</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Fuzzy Number-Valued Fuzzy Graph</ArticleTitle>
<VernacularTitle>گراف فازی با مقدار عدد فازی مقدار</VernacularTitle>
			<FirstPage>77</FirstPage>
			<LastPage>86</LastPage>
			<ELocationID EIdType="pii">3400</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Siyamak</FirstName>
					<LastName>Firouzian</LastName>
<Affiliation>Department of Mathematics, Payame Noor University (PNU) Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohamad</FirstName>
					<LastName>Adabitabar Firozja</LastName>
<Affiliation>Department of mathematics, Qaemshar Branch, Islamic Azad University, Qaemshahr, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>11</Day>
				</PubDate>
			</History>
		<Abstract>Graph theory has an important role in the area of applications of networks and clustering‎. ‎In the case of dealing with uncertain data‎, ‎we must utilize ambiguous data such as fuzzy value‎, ‎fuzzy interval value or values of fuzzy number‎. ‎In this study‎, ‎values of fuzzy number were used‎. ‎Initially‎, ‎we utilized the fuzzy number value fuzzy relation and then proposed fuzzy number-value fuzzy graph on nodes and arcs‎. ‎In this study‎, ‎some properties of the graph on fuzzy number-value fuzzy graph were examined‎. ‎First‎, ‎we define the Cartesian product‎, ‎composition‎, ‎union and join operators on fuzzy number-value fuzzy graphs and then prove some of their properties and and give some examples for every one of definitions‎. ‎We also introduced the notion of homomorphism‎, ‎weak isomorphism,weak co-isomorphism‎, ‎isomorphism‎, ‎complete‎, ‎weak complete and compliment on the fuzzy number fuzzy graphs and prove some of their properties and also present some examples for every one of them.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">Fuzzy numbers‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Relation‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Fuzzy relation‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Graph‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Fuzzy graph</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mathco.journals.pnu.ac.ir/article_3400_454ff85596b1356c9aa00b9fcbbcae7f.pdf</ArchiveCopySource>
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