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Fuzzy Computing in Data Science

Om Fuzzy Computing in Data Science

FUZZY COMPUTING IN DATA SCIENCE This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges. The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation. Audience Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.

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  • Språk:
  • Engelska
  • ISBN:
  • 9781119864929
  • Format:
  • Inbunden
  • Sidor:
  • 368
  • Utgiven:
  • 16. november 2022
  • Mått:
  • 440x159x27 mm.
  • Vikt:
  • 672 g.
  Fri leverans
Leveranstid: 2-4 veckor
Förväntad leverans: 15. september 2025

Beskrivning av Fuzzy Computing in Data Science

FUZZY COMPUTING IN DATA SCIENCE
This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges.
The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation.
Audience
Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.

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