<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-information-and-optimization-sciences</journal-id>
      <journal-title-group>
        <journal-title>Journal of Information and Optimization Sciences</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0103</issn>
      <issn publication-format="print">0252-2667</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JIOS-1415</article-id>
      <title-group>
        <article-title>Consumer product prediction using machine learning</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Ajitha</surname>
            <given-names>P.</given-names>
          </name>
          <aff>School of Computing, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Tamilvizhi</surname>
            <given-names>T.</given-names>
          </name>
          <aff>Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Sowjanya</surname>
            <given-names>K. Naga</given-names>
          </name>
          <aff>Department of Information Technology, Vel Tech Multi Tech Dr. Rangarajan Dr.Sakunthala Engineering College, Chennai, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Surendran</surname>
            <given-names>R.</given-names>
          </name>
          <aff>Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bala</surname>
            <given-names>Bhoomeshwar</given-names>
          </name>
          <aff>Department of Computer Science, Debre Tabor University, Debra Tabor, Ethiopia</aff>
        </contrib>
      </contrib-group>
      <volume>44</volume>
      <issue>3</issue>
      <fpage>565</fpage>
      <lpage>574</lpage>
      <pub-date date-type="pub">
        <day>11</day>
        <month>08</month>
        <year>2023</year>
      </pub-date>
      <abstract>
        <p>Time-series forecasting is an approach that uses historical and current data to project future values over time or at a given point in time, while forecasting and prediction are often synonymous, there is one interesting detail. In some professions, forecasting may refer to data at a specific future point in time, whereas prediction refers to future data in general. Most widely used to determine the nature of stock prices. A series of analyses and modeling by a finance committee is to guide investors, professors of legal sciences, and processes. And that is why he proposes that this series argument not include a sliding window; they were wise to back then, and they gave up everything, anticipating stock values relative to her. The system presents the (GUI) Graphical User Interface as a stand-alone application. The proposed findings demonstrate a highly predicted accurate approach for nonlinear time series models that are difficult to obtain from traditional models.</p>
      </abstract>
      <kwd-group>
        <kwd>Machine learning</kwd>
        <kwd>Prediction</kwd>
        <kwd>Neural network</kwd>
        <kwd>Backpropagation</kwd>
        <kwd>Support vector machine</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
