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  <doi_batch_id>aspg-18-766-1792025543</doi_batch_id>
  <timestamp>20261015005223</timestamp>
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  <journal>
   <journal_metadata language="en">
    <full_title>Journal of Intelligent Systems and Internet of Things</full_title>
    <abbrev_title>JISIoT</abbrev_title>
    <issn media_type="print">2769-786X</issn>
    <issn media_type="electronic">2690-6791</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2021</year>
    </publication_date>
    <journal_volume>
     <volume>5</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Intelligent System for Forecasting Failure of Agile Projects</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Ahmed Abdelaziz and Alia N</given_name>
      <surname>Mahmoud</surname>
      <affiliations>
       <institution>
        <institution_name>Nova Information Management School, Universidade Nova de Lisboa, 1070-312, Lisboa, Portugal</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Revealing the failure of agile software projects is a great challenge faced by software companies. This paper focuses on the using of intelligent techniques such as fuzzy logic, multiple linear regressions, support vector machine, neural network to address this challenge. This paper also presents a review of some works related to this area of interest. In this paper, the researchers propose an approach for revealing the failure of agile software projects based on two intelligent techniques: fuzzy logic and multiple linear regressions (MLR). MLR is used to determine crucial failure factors of agile software projects. Fuzzy logic is used for revealing failure of agile software projects.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2021</year>
    </publication_date>
    <pages>
     <first_page>08</first_page>
     <last_page>19</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">766</item_number>
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     <doi>10.54216/JISIoT.050102</doi>
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