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    <name>Article</name>
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          <name>Title</name>
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              <text>Performance evaluation of artificial neural networks in sustainable modelling biodiesel synthesis</text>
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          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>Absolute average deviation (AAD); Biodiesel; Catalyst concentration; Fatty acid methyl ester (FAME); Genetic algorithm; Machine learning (ML); Response surface methodology (RSM); Transesterification</text>
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              <text>Biodiesel is a characteristic and inexhaustible homegrown fuel removed from creature fats or vegetable oil and liquor through a transesterification response. The exploration work means to assess the exhibition of biodiesel blend. In this paper, biodiesel was displayed and improved by utilizing a hereditary calculation and Artificial Neural Network (ANN). In AI, hereditary calculations and counterfeit neural organizations assume a significant part in displaying biodiesel blend. To upgrade an excellent arrangement hereditary calculation was created. The mix of ANN and Genetic Algorithm gives the ideal condition as the temperature of methanol molar proportion, impetus fixation. It tentatively decides the exhibition trademark like the Coefficient of determination and Absolute Average deviation (AAD). It predicts the Fatty Acid Methyl Ester (FAME) model productively than Response Surface Methodology (RSM). The exhibition examination is reenacted and hypothetical outcomes are recorded then it is contrasted with constant information to decide the exactness of ANN.  2022 Elsevier Ltd</text>
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          <name>Creator</name>
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              <text>Treve M.; Patra I.; Prabu P.; Rama Sree S.; Keerthi Kumar N.; Methkal Abd Algani Y.; Kiran Bala B.; Balaji S.</text>
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          <name>Source</name>
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              <text>Sustainable Energy Technologies and Assessments, Vol-52</text>
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          <name>Publisher</name>
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              <text>Elsevier Ltd</text>
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          <name>Date</name>
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              <text>2022-01-01</text>
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          <name>Identifier</name>
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              <text>&lt;a href="https://doi.org/10.1016/j.seta.2022.102098" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.seta.2022.102098&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125008191&amp;amp;doi=10.1016%2Fj.seta.2022.102098&amp;amp;partnerID=40&amp;amp;md5=3d6d2154f2fa983572b596d41de021de" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125008191&amp;amp;doi=10.1016%2fj.seta.2022.102098&amp;amp;partnerID=40&amp;amp;md5=3d6d2154f2fa983572b596d41de021de&lt;/a&gt;</text>
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          <name>Rights</name>
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            <elementText elementTextId="106080">
              <text>Restricted Access</text>
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              <text>ISSN: 22131388</text>
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          <name>Format</name>
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              <text>Online</text>
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          <name>Language</name>
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              <text>English</text>
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              <text>Article</text>
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              <text>Treve M., School of Languages and General Education, Walailak University, Thailand; Patra I., An Independent Researcher and Ex-research Scholar at NIT Durgapur, West Bengal, India; Prabu P., Department of Computer Science, CHRIST(Deemed to be University), Bangalore, India; Rama Sree S., Professor in CSE Dept., Aditya Engineering College, Andhra Pradesh, Surampalem, India; Keerthi Kumar N., Department of Mechanical Engineering, BMS Institute of Technology and Management, Avalahalli, Doddaballapur Main Road, Yelahanka, Bangalore, 560064, India; Methkal Abd Algani Y., Department of Mathematics, Sakhnin College, Israel, Department of Mathematics, The Arab Academic College for Education in Israel-Haifa, Israel; Kiran Bala B., Department of Artificial Intelligence and Data Science, K. Ramakrishnan College of Engineering, Tamil Nadu, Trichy, India; Balaji S., Department of CSE, Panimalar Engineering College, Tamil Nadu, Chennai, India</text>
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