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Autor(en): 
  • Chris Harris
  • Xia Hong
  • Qiang Gan
  • Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2012  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / Automated Pattern Recognition / C / computer science / Computer science—Mathematics / Computers / Data Warehousing / Information Retrieval
    ISBN:  9783642621192 
    EAN-Code: 
    9783642621192 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Advanced Information Processing  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  522 gr 
    Seiten:  323 
    Illustration:  XVI, 323 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input.

    This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency.

    Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

      



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