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Herausgeber: 
  • Roger Lee
  • Miltos Petridis
  • Liz Bacon
  • Wencai Du
  • Jixin Ma
  • Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2010 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2010  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Artificial Intelligence / B / Computational Intelligence / Design / Development / Distributed Computing / engineering / intelligence
    ISBN:  9783642132643 
    EAN-Code: 
    9783642132643 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  #295 - Studies in Computational Intelligence  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  940 gr 
    Seiten:  166 
    Illustration:  X, 166 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    th The purpose of the 11 Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2010) held on June 9 - 11, 2010 in London, United Kingdom was to bring together researchers and scientists, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 15 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rounds of rigorous review. In Chapter 1, Cai Luyuan et al. Present a new method of shape decomposition based on a refined morphological shape decomposition process. In Chapter 2, Kazunori Iwata et al. propose a method for reducing the margin of error in effort and error prediction models for embedded software development projects using artificial neural networks (ANNs). In Chapter 3, Viliam simko et al. describe a model-driven tool that allows system code to be generated from use-cases in plain English. In Chapter 4, Abir Smiti and Zied Elouedi propose a Case Base Maintenance (CBM) method that uses machine learning techniques to preserve the maximum competence of a system. In Chapter 5, Shagufta Henna and Thomas Erlebach provide a simulation based analysis of some widely used broadcasting schemes within mobile ad hoc networks (MANETs) and propose adaptive extensions to an existing broadcasting algorithm.

      



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