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Herausgeber: 
  • Pradip Debnath
  • Binod Chandra Tripathy
  • Soft Computing: Engineering Applications 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2026  
    Genre:  EDV / Informatik 
     
    Algorithms & data structures / algorithms and data structures / Artificial Intelligence / Artificial Intelligence (AI) / Automatic control engineering / big data visualization / Cloud Computing / Computational Intelligence
    ISBN:  9781032738512 
    EAN-Code: 
    9781032738512 
    Verlag:  Taylor and Francis 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D  
    Gewicht:  680 gr 
    Seiten:  356 
    Illustration:  schwarz-weiss Illustrationen 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    This book examines the latest developments in the area of soft computing with engineering applications. It explores topics such as fuzzy sets, intuitionistic fuzzy sets, unmanned aerial vehicles, soft sets, neutrosophic sets, fractional calculus, big data analytics, and the mathematical foundations of convolutional neural network (CNNs). Soft Computing: Engineering Applications offers readers a comprehensive and in-depth understanding of various cutting-edge technologies that are transforming industries worldwide.

    The book explores soft computing techniques in a very systematic manner. It elucidates the concepts, theories, and applications of fuzzy sets, enabling readers to grasp the fundamentals and explore their applications in various fields. It provides new insight into unmanned aerial vehicle applications to fuzzy soft set based decision making. It then discusses new fixed point results in orthogonal neutrosophic generalized metric spaces and explores statistical convergence of triple sequences in a credibility space. The authors then provide readers with a solid grasp of the mathematical underpinnings of CNNs, enabling them to design, train, and optimize neural networks for image recognition, object detection, and other computer vision tasks. The authors also present new studies in fractional calculus and explores advanced visualization algorithms and techniques for big data analytics.

    Soft Computing will be useful for beginners and advanced researchers in engineering, applied sciences and healthcare professionals working in soft computing applications.

      



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