February 29, 2020 Journal article Open Access

M. Alagurajan; C. Vijayakumaran

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  <identifier identifierType="URL">https://zenodo.org/record/5593844</identifier>
  <creators>
    <creator>
      <creatorName>M. Alagurajan</creatorName>
      <affiliation>Department of CSE, SRM Institute of Science and  Technology, Chennai, Tamil Nadu, India.</affiliation>
    </creator>
    <creator>
      <creatorName>C. Vijayakumaran</creatorName>
      <affiliation>Associate Professor, Department CSE, SRM  Institute of Science and Technology, Chennai, Tamil Nadu, India.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>ML Methods for Crop Yield Prediction and  Estimation: An Exploration</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Machine Learning, Crop Yield,</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">C5775029320/2020©BEIESP</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  &amp; Sciences Publication(BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2020-02-29</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5593844</alternateIdentifier>
  </alternateIdentifiers>
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    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.C5775.029320</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;Machine learning Has performed a essential position within the estimation of crop yield for both farmers and consumers of the products. Machine learning techniques learn from data set related to the environment on which the estimations and estimation are to be made and the outcome of the learning process are used by farmers for corrective measures for yield optimization. This paper we explore various ML techniques utilized in crop yield estimation and provide the detailed analysis of accuracy of the techniques.&lt;/p&gt;</description>
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