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Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK 2020 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 556 pages, kõrgus x laius: 235x155 mm, kaal: 866 g, 159 Illustrations, color; 67 Illustrations, black and white; XV, 556 p. 226 illus., 159 illus. in color., 1 Paperback / softback
  • Sari: Advances in Intelligent Systems and Computing 1043
  • Ilmumisaeg: 30-Aug-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030299325
  • ISBN-13: 9783030299323
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  • Pehme köide
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  • Formaat: Paperback / softback, 556 pages, kõrgus x laius: 235x155 mm, kaal: 866 g, 159 Illustrations, color; 67 Illustrations, black and white; XV, 556 p. 226 illus., 159 illus. in color., 1 Paperback / softback
  • Sari: Advances in Intelligent Systems and Computing 1043
  • Ilmumisaeg: 30-Aug-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030299325
  • ISBN-13: 9783030299323
Teised raamatud teemal:
This book highlights the latest research in computational intelligence and its applications. It covers both conventional and trending approaches in individual chapters on Fuzzy Systems, Intelligence in Robotics, Deep Learning Approaches, Optimization and Classification, Detection, Inference and Prediction, Hybrid Methods, Emerging Intelligence, Intelligent Health Care, and Engineering Data- and Model-Driven Applications. All chapters are based on peer-reviewed contributions presented at the 19th Annual UK Workshop on Computational Intelligence, held in Portsmouth, UK, on 46 September 2019.





The book offers a valuable reference guide for readers with expertise in computational intelligence or who are seeking a comprehensive and timely review of the latest trends in computational intelligence. Special emphasis is placed on novel methods and their use in a wide range of application areas, updating both academics and professionals on the state of the art.
Fuzzy Systems.- Intelligence in Roobtics.- Deep Learning
Approaches.- Optimisation and Classification.- Detection, Inference and
Prediction.- Hybrid Methods.- Emerging Intelligence.- Intelligent
Healthcare.- Engineering Data- and Model-Driven Applications.