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Computational Intelligence in Machine Learning

Bag om Computational Intelligence in Machine Learning

This volumes comprises select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2022). The contents cover latest research trends and developments in the areas of machine learning, smart cities, IoT, Artificial Intelligence, cyber physical systems, cybernetics, data science, neural network, cognition, among others. It also addresses the comprehensive nature of computational intelligence, AI, ML and DL to emphasize its character in modelling, identification, optimization, prediction, forecasting, and control of future intelligent systems. This volume will be a useful guide to those working as researchers in academia and industry by presenting in-depth fundamental research contributions from a methodological/application perspective in understanding Artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789819979530
  • Indbinding:
  • Hardback
  • Sideantal:
  • 720
  • Udgivet:
  • 21. februar 2024
  • Udgave:
  • 24001
  • Størrelse:
  • 160x42x241 mm.
  • Vægt:
  • 1363 g.
  • Ukendt - mangler pt..
Forlænget returret til d. 31. januar 2025

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- Adgang til 70.000+ titler
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Beskrivelse af Computational Intelligence in Machine Learning

This volumes comprises select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2022). The contents cover latest research trends and developments in the areas of machine learning, smart cities, IoT, Artificial Intelligence, cyber physical systems, cybernetics, data science, neural network, cognition, among others. It also addresses the comprehensive nature of computational intelligence, AI, ML and DL to emphasize its character in modelling, identification, optimization, prediction, forecasting, and control of future intelligent systems. This volume will be a useful guide to those working as researchers in academia and industry by presenting in-depth fundamental research contributions from a methodological/application perspective in understanding Artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications.

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