<?xml version="1.0"?>
<records>
  <record>
    <language>eng</language>
    <publisher>Ansari Education and Research Society</publisher>
    <journalTitle>Journal of Ultra Scientist of Physical Sciences</journalTitle>
    <issn/>
    <eissn/>
    <publicationDate>August 2009</publicationDate>
    <volume>21</volume>
    <issue>2</issue>
    <startPage>521</startPage>
    <endPage>530</endPage>
    <doi>jusps-A</doi>
    <publisherRecordId>1219</publisherRecordId>
    <documentType>article</documentType>
    <title language="eng">Optimization of fuzzy expert systems using neural network in decision-making in competitive situation&#xA0;</title>
    <authors>
      <author>
        <name>P.K. Parida (prashanta_math@yahoo.co.in</name>
        <affiliationId>1</affiliationId>
      </author>
      <author>
        <name>S.K. Sahoo (sahoosk1@rediffmail.com)</name>
        <affiliationId>2</affiliationId>
      </author>
    </authors>
    <affiliationsList>
      <affiliationName affiliationId="1">Eastern Academy of Science &amp; Technology</affiliationName>
      <affiliationName affiliationId="2">Institute of Mathematics &amp; Applications Andhra Pradesh, Nhubanseswa-3 Orissa (India)</affiliationName>
    </affiliationsList>
    <abstract language="eng">&lt;p style="text-align:justify"&gt;Many decision making problems may be solved with Heuristic search algorithms. Expert systems taking decisions in competitive situation in uncertain environment/fuzzy environment may take a graph-search algorithm to tackle the situation. To improve the performance of the overall system, a set of important parameters of the decision making system is identified. Optimization methods such as Neural Network (N.N.) is used for the learning of the optimum parameters and also for an improvement of the performance.&lt;/p&gt;&#xD;
&#xD;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;&#xD;
&#xD;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;&#xD;
</abstract>
    <fullTextUrl format="html">https://www.ultrascientist.org/paper/1219/</fullTextUrl>
    <keywords>
      <keyword language="eng">Fuzzy logic</keyword>
    </keywords>
    <keywords>
      <keyword language="eng">Defuzzification</keyword>
    </keywords>
    <keywords>
      <keyword language="eng">Neural Network (N.N.).u00a0</keyword>
    </keywords>
  </record>
</records>
