Input Handling Agent Based by Fayyaz Muhammad (4 results)

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    • Language: English

      Published by LAP Lambert Academic Publishing, 2013

      365933300X / 9783659333002

      • Softcover

      Seller: preigu, Osnabrück, Germanypreigu

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      Taschenbuch. Condition: Neu. Input handling in agent based micro level simulators | Muhammad Saleem Fayyaz | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659333002 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2013

      365933300X / 9783659333002

      • Softcover

      Seller: Mispah books, Redhill, SURRE, United KingdomMispah books

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      paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2013

      365933300X / 9783659333002

      • Softcover
      • Print on Demand

      Seller: moluna, Greven, Germanymoluna

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      Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Fayyaz Muhammad SaleemM. Saleem Fayyaz, MSc: studied computer science at Blekinge institute of technology, Sweden. Has experiences from Uiq, Sony Ericsson and Samsung. Has research interest in theoretical and foundations of computer .

    • Language: English

      Published by LAP Lambert Academic Publishing, 2013

      365933300X / 9783659333002

      • Softcover
      • Print on Demand

      Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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      Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A new approach is presented for handling missing values in multi-level agent-based simulation (MABS) at micro-level by using truth tables and logical relations. Although micro-level simulation is a vast field to use logical relations with truth tables to find missing values but it takes values into account at individual levels. We used databases in form of tables to extract missing values. We have defined logical relations according to scenario by interacting with truth tables to find appropriate missing values. In this research we have concluded that missing values would be handled in different ways, such as: Artificial neural network, K-nearest neighbor, Statistical method and Data mining; etc These methods have not facilitated in finding appropriate missing values as we saw in literature. We have created a method that can find missing values and produce good results. We have run our method on a specific scenario to check the efficiency of input handling that motivated us to arrange database in a proper way to handle missing values along.