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  <doi_batch_id>aspg-25-1777-1791492977</doi_batch_id>
  <timestamp>20261008205617</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <registrant>American Scientific Publishing Group</registrant>
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  <journal>
   <journal_metadata language="en">
    <full_title>Journal of Cognitive Human-Computer Interaction</full_title>
    <abbrev_title>JCHCI</abbrev_title>
    <issn media_type="print">2771-1471</issn>
    <issn media_type="electronic">2771-1463</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2023</year>
    </publication_date>
    <journal_volume>
     <volume>5</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Earthquake Location Forecasting In Map Using XGBOOST Algorithm</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>R.</given_name>
      <surname>Jeena</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Information Technology, Panimalar Institute of Technology, Chennai, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Kruthika</given_name>
      <surname>M.</surname>
      <affiliations>
       <institution>
        <institution_name>UG Scholar, Department of Information Technology, Panimalar Institute of Technology, Chennai, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Princy</given_name>
      <surname>A.</surname>
      <affiliations>
       <institution>
        <institution_name>UG Scholar, Department of Information Technology, Panimalar Institute of Technology, Chennai, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Tanya</given_name>
      <surname>A.</surname>
      <affiliations>
       <institution>
        <institution_name>UG Scholar, Department of Information Technology, Panimalar Institute of Technology, Chennai, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Earthquake is one of the most threatening natural disasters which is caused due to the shaking of the earth’s surface. Common cause of earthquake is due to ground shaking, underground volcanic eruption. Here, XGBoost Algorithm is used to predict the location of the earthquake. In this paper, a earthquake location prediction method is proposed, which is based on the composition of a known system whose behaviour is administered according to the evaluation of more than two decades of seismic events and is designed as a time series using Machine learning. By analyzing the parameters such as Latitude, Magnitude, Depth, Longitude, Depth error, Gap, Time etc.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2023</year>
    </publication_date>
    <pages>
     <first_page>42</first_page>
     <last_page>45</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1777</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/JCHCI.050104</doi>
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