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    <title>Tutmez, B.</title>
    <link>http://repub.eur.nl/res/aut/16339/</link>
    <description>List of Publications</description>
    <language>en</language>
    <image>
      <url>http://repub.eur.nl/static-eur/img/logo.png</url>
      <title>RePub, Erasmus University Rotterdam</title>
      <link>http://repub.eur.nl</link>
    </image>
    <item>
      <title>Fuzzy optimization of slab production from mechanical stone properties (Article)</title>
      <link>http://repub.eur.nl/res/pub/14254/</link>
      <pubDate>2008-12-01T00:00:00Z</pubDate>
      <description>This paper aims to conduct slab production optimization by a flexible tool, which is fuzzy linear programming. There is a direct relationship between slab production and mechanical stone characteristics. In this process, the goal and its tolerance cannot be specified firstly due to a lack of knowledge. Therefore, the optimal system design problem for optimal slab production under soft constraints is constructed and solved in a fuzzy environment. The results show that fuzzy linear optimization is a convenient tool for optimizing slab production. © 2008 Springer-Verlag.</description>
    </item> <item>
      <title>Measure of uncertainty in regional grade variability (Article)</title>
      <link>http://repub.eur.nl/res/pub/15855/</link>
      <pubDate>2007-12-01T00:00:00Z</pubDate>
      <description>Because the geological events are neither homogeneous nor isotropic, the geological investigations are characterized by particularly high uncertainties. This paper presents a hybrid methodology for measuring of uncertainty in regional grade variability. In order to evaluate the fuzziness in grade values at ore deposit, point cumulative semimadogram (PCSM) measure and a metric distance have been employed. By using the experimental PCSMs and their linear models, measures of fuzziness have been carried out for each location. Finally, an uncertainty map, which defines the regional variation of the uncertainty in different categories, has been composed.</description>
    </item> <item>
      <title>Fuzzy Modeling for Reserve Estimation Based on Spatial Variability (Article)</title>
      <link>http://repub.eur.nl/res/pub/19258/</link>
      <pubDate>2007-01-01T00:00:00Z</pubDate>
      <description>This article addresses a new reserve estimation method which uses fuzzy modeling algorithms and estimates the reserve parameters based on spatial variability. The proposed fuzzy modeling approach has three stages: (1) Structure identification and preliminary clustering, (2) Variogram analysis, and (3) Clustering based rule system. A new clustering index approach and a new spatial measure function (point semimadogram) are proposed in the paper. The developed methodology uses spatial variability in each step and takes the fuzzy rules from input-output data. The model has been tested using both simulated and real data sets. The performance evaluation indicates that the new methodology can be applied in reserve estimation and similar modeling problems .</description>
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