<?xml version="1.0" encoding="UTF-8"?>
<doi_batch version="5.3.1" xmlns="http://www.crossref.org/schema/5.3.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schema/deposit/crossref5.3.1.xsd">
 <head>
  <doi_batch_id>aspg-28-1411-1792155171</doi_batch_id>
  <timestamp>20261016125251</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
  </depositor>
  <registrant>American Scientific Publishing Group</registrant>
 </head>
 <body>
  <journal>
   <journal_metadata language="en">
    <full_title>Journal of Artificial Intelligence and Metaheuristics</full_title>
    <abbrev_title>JAIM</abbrev_title>
    <issn media_type="electronic">2833-5597</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <journal_volume>
     <volume>2</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Evaluating the Effect of Optimized Voting Using Hybrid Particle Swarm and Grey Wolf Algorithm on the Classification of the Zoo Dataset</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Doaa S.</given_name>
      <surname>Khafaga</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Hussein</given_name>
      <surname>Alkattan</surname>
      <affiliations>
       <institution>
        <institution_name>Department of System Programming South Ural State University; pr. Lenina 76, Chelyabinsk, 454080 Russia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Alhumaima A.</given_name>
      <surname>Subhi</surname>
      <affiliations>
       <institution>
        <institution_name>Electronic and Computer Center, University of Diyala, Baqubah MJJ2+R9G, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>When there are numerous possible solutions for a given class in a given problem, majority voting or plurality voting is typically employed. One common technique for improving classification accuracy is bagging, which involves training many classifiers on slightly different datasets and then voting on the combined results. In this research, we examine how alternative voting procedures affect the efficiency of two distinct classification algorithms applied to datasets of varying complexity. Despite the increased computing cost associated with determining preference order, the results show that the single transferable vote can be a suitable alternative to plurality voting.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>08</first_page>
     <last_page>15</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1411</item_number>
    </publisher_item>
    <ai:program name="AccessIndicators">
     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/JAIM.020101</doi>
     <resource>https://www.americaspg.com/journal/28/article/1411</resource>
     <collection property="text-mining">
      <item>
       <resource mime_type="application/pdf">https://www.americaspg.com/storage/71670830496.pdf</resource>
      </item>
     </collection>
    </doi_data>
   </journal_article>
  </journal>
 </body>
</doi_batch>
