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Herausgeber: 
  • Ajith Abraham
  • Crina Grosan
  • Vitorino Ramos
  • Swarm Intelligence in Data Mining 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2006  
    Genre:  EDV / Informatik 
     
    Applied mathematics / Artificial Intelligence / B / Computers / engineering / Engineering mathematics / Mathematical and Computational Engineering / Mathematical and Computational Engineering Applications / Mathematical theory of computation / Maths for engineers / Theory of Computation
    ISBN:  9783540349556 
    EAN-Code: 
    9783540349556 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  653 gr 
    Seiten:  268 
    Illustration:  XVIII, 268 p. 91 illus., 5 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Swarm Intelligence is an innovative distributed intelligent paradigm for solving optimization problems that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates. Data Mining is an analytic process designed to explore large amounts of data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.

    This book deals with the application of swarm intelligence in data mining. Addressing the various issues of swarm intelligence and data mining using different intelligent approaches is the novelty of this edited volume. This volume comprises of 11 chapters including an introductory chapter giving the fundamental definitions and some important research challenges.

    Important features include the detailed overview of the various swarm intelligence and data mining paradigms, excellent coverage of timely, advanced data mining topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as well as engineers engaged in research, development and application of optimization techniques and data mining will find the comprehensive coverage of this book invaluable.

      
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