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Herausgeber: 
  • Luis Magdalena
  • O. Cordón
  • Jorge Casillas
  • Francisco Herrera Triguero
  • Accuracy Improvements in Linguistic Fuzzy Modeling 
     

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


    Übersicht

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    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Dezember 2010  
    Genre:  Wirtschaft / Recht 
     
    Applied Dynamical Systems / Applied mathematics / Artificial Intelligence / Business Mathematics / C / complexity / Computational complexity / Cybernetics & systems theory / Economic Theory / Economic theory & philosophy / Economic Theory/Quantitative Economics/Mathematical Methods / engineering / Engineering mathematics / Management science / Mathematical and Computational Engineering / Mathematical and Computational Engineering Applications / Maths for engineers / Natural language & machine translation / Natural language processing (Computer science) / Natural Language Processing (NLP) / Quantitative Economics
    ISBN:  9783642057038 
    EAN-Code: 
    9783642057038 
    Verlag:  Springer Berlin Heidelberg 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #129 - Studies in Fuzziness and Soft Computing  
    Dimensionen:  H 235 mm / B 155 mm / D 22 mm 
    Gewicht:  604 gr 
    Seiten:  400 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Fuzzy modeling usually comes with two contradictory requirements: interpretability, which is the capability to express the real system behavior in a comprehensible way, and accuracy, which is the capability to faithfully represent the real system. In this framework, one of the most important areas is linguistic fuzzy modeling, where the legibility of the obtained model is the main objective. This task is usually developed by means of linguistic (Mamdani) fuzzy rule-based systems. An active research area is oriented towards the use of new techniques and structures to extend the classical, rigid linguistic fuzzy modeling with the main aim of increasing its precision degree. Traditionally, this accuracy improvement has been carried out without considering the corresponding interpretability loss. Currently, new trends have been proposed trying to preserve the linguistic fuzzy model description power during the optimization process. Written by leading experts in the field, this volume collects some representative researcher that pursue this approach.

      
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