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  <front>

    <journal-meta>

      <journal-title>Information Technology Journal</journal-title>

      <issn pub-type="ppub">1812-5638</issn>

      <issn pub-type="epub">1812-5646</issn>

      <publisher>

        <publisher-name>Asian Network for Scientific Information</publisher-name>

      </publisher>

    </journal-meta>


    <article-meta>

      <article-id pub-id-type="doi">10.3923/itj.2012.554.556</article-id>


      <title-group>

        <article-title><![CDATA[VO Algorithm and It&#146;s an Application for the Locations of Tailings Dam]]></article-title>

      </title-group>


      <contrib-group>

        <contrib contrib-type="author" xlink:type="simple">


          <name name-style="western">

            <surname>Hong-xu</surname>

            <given-names>Wang</given-names>

          </name>


        </contrib>

      </contrib-group>


      <pub-date pub-type="collection">


        <month>4</month>




        <year>2012</year>

      </pub-date>


      <volume>11</volume>

      <issue>4</issue>


      <abstract><![CDATA[<p>Given a transforming formula from the single value data to vague data. And presented a similarity measure formula between vague sets. In choosing location of tailings dam, the detailed steps of the VO algorithm are that: (1) Establish an index set; (2) Screen out the locations of tailings dam; (3) Draw an expectation location of tailings dam; (4) Get into vague environment. The original data turn the vague data. Get vague sets of the locations of tailings dam and vague set of a expectation location of tailings dam; (5) Calculate similarity measures. Calculate similarity measures between vague sets of the locations of tailings dam and vague set of a expectation location of tailings dam; (6) Vague optimize sort. By the numerical size of the similarity measures can be the sorts. Vague sort: similarity measures corresponding to those in greatest numerical size that is the best a location of tailings dam. The application example shows that this algorithm and these formulas are useful.</p>]]></abstract>


    </article-meta>

  </front>


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</article>

