June 30, 2020 Journal article Open Access

S. Aicevarya Devi; C. Vijayalakshmi

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  <identifier identifierType="URL">https://zenodo.org/record/5546719</identifier>
  <creators>
    <creator>
      <creatorName>S. Aicevarya Devi</creatorName>
      <affiliation>Mathematics division, School of Advanced Science,  Vellore Institute of Technology, Chennai, Tamil Nadu.</affiliation>
    </creator>
    <creator>
      <creatorName>C. Vijayalakshmi</creatorName>
      <affiliation>Mathematics division, School of Advanced Science,  Vellore Institute of Technology, Chennai, Tamil Nadu.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Unmanned Aerial Vehicle Path Planning using  Bat Algorithm</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Bat algorithm, Unmanned Aerial Vehicle, Population, Path planning, Frequency, Position.</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">E9285069520/2020©BEIESP</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-06-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5546719</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.E9285.069520</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Unmanned Aerial Vehicles (UAV) was introduced after World War II. In 1980&amp;rsquo;s UAV consider as important weapon system. Initially UAV needs initial position and target position. In this paper bat algorithm is proposed with mixed objective constraints which helps in directing the UAV. The process is initialized by generating the initial population of bat. Then by updating the population size and generation of bat the fitness value with minimum frequency is found that helps to avoid convergence among UAV. Finally the evaluation which gives minimum frequency is considered as optimal solution.&lt;/p&gt;</description>
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