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Big Data Intelligence for Smart Applications 2022 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 334 pages, kõrgus x laius: 235x155 mm, kaal: 534 g, 80 Illustrations, color; 34 Illustrations, black and white; XI, 334 p. 114 illus., 80 illus. in color., 1 Paperback / softback
  • Sari: Studies in Computational Intelligence 994
  • Ilmumisaeg: 20-Jan-2023
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030879569
  • ISBN-13: 9783030879563
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  • Pehme köide
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Big Data Intelligence for Smart Applications 2022 ed.Suurem pilt
  • Formaat: Paperback / softback, 334 pages, kõrgus x laius: 235x155 mm, kaal: 534 g, 80 Illustrations, color; 34 Illustrations, black and white; XI, 334 p. 114 illus., 80 illus. in color., 1 Paperback / softback
  • Sari: Studies in Computational Intelligence 994
  • Ilmumisaeg: 20-Jan-2023
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030879569
  • ISBN-13: 9783030879563
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783030879563.html
Märksõnad:
Today, the use of machine intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines.  As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity.

This book presents the latest advances in big data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

Data Quality in the Era of Big Data: A Global Review.- Adversarial
Machine Learning, Research Trends and Applications.- Multi-agent Systems for
Distributed Data Mining Techniques: An Overview.- Time Series Data Analysis
using Deep Learning methods for Smart Cities monitoring.- A Low-Cost
IMU-Based Wearable System for Precise Identification of Walk Activity using
Deep Convolutional Neural Network.