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  <doi_batch_id>aspg-41-3849-1792225907</doi_batch_id>
  <timestamp>20261017083147</timestamp>
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  <journal>
   <journal_metadata language="en">
    <full_title>Metaheuristic Optimization Review</full_title>
    <abbrev_title>MOR</abbrev_title>
    <issn media_type="electronic">3066-280X</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <journal_volume>
     <volume>4</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Optimization of Carbon Dioxide Emissions Reduction Using Artificial Intelligence: A Review for Industrial and Electric Vehicle Perspectives</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Omnia M.</given_name>
      <surname>Osama</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Marwa M.</given_name>
      <surname>Eid</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura 35111, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>El-Sayed M. El</given_name>
      <surname>Rabaie</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Electronic Engineering, Menouﬁa University, Department of Electronics and Communications, Menouf 32952, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Artificial intelligence systems are revolutionizing how industries reduce carbon dioxide emissions in numerous business fields. This study combines research on how artificial intelligence merges with carbon reduction methods, specifically in industrial procedures and electric vehicle manufacturing, with an environmental sustainability focus. Multiple empirical studies and advanced AI models provide insight into sustainability effects caused by AI systems and emission decrease processes. AI technology performs three essential functions to enhance energy optimization pro, mote eco-friendly research, and improve environmental prediction accuracy. The identified information provides essential guidance to policymakers and industrial leaders about AI applications for achieving zero emissions and sustainability targets. The review presents evidence that AI technology can redefine sustainability throughout vehicle production while managing transportation and other fields thus helping solve escalating climate issues and drive eco-friendly developments.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <pages>
     <first_page>14</first_page>
     <last_page>18</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">3849</item_number>
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     <doi>10.54216/MOR.040104</doi>
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