Kruse, R: Computational Intelligence
indgår i Texts in Computer Science serien
- Indbinding:
- Paperback
- Sideantal:
- 656
- Udgivet:
- 30. marts 2023
- Udgave:
- 23003
- Størrelse:
- 155x36x235 mm.
- Vægt:
- 978 g.
- 8-11 hverdage.
- 16. januar 2025
På lager
Forlænget returret til d. 31. januar 2025
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- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
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- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Kruse, R: Computational Intelligence
This textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced third edition has been fully revised and expanded with new content on deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms.
Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.
Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.
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