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      Fractional Dynamics of Genetic Algorithms Using Hexagonal Space Tessellation

      Abstract and Applied Analysis
      Hindawi Limited

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          Abstract

          The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.

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          Fractional-order systems and PI/sup /spl lambda//D/sup /spl mu//-controllers

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            Preface

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              Recent history of fractional calculus

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                Author and article information

                Journal
                Abstract and Applied Analysis
                Abstract and Applied Analysis
                Hindawi Limited
                1085-3375
                1687-0409
                2013
                2013
                : 2013
                :
                : 1-7
                Article
                10.1155/2013/739464
                8a18c1e7-465e-49ba-9b59-df96b257ddd1
                © 2013

                http://creativecommons.org/licenses/by/3.0/

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