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Computational Methods for Application in Industry 4.0 / by Nikolaos E. Karkalos, Angelos P. Markopoulos, J. Paulo Davim

By: Karkalos, Nikolaos E., autor
Contributor(s): SpringerLink (Online service) | Davim, J. Paulo, autor | Markopoulos, Angelos P., (1976-), autor
Series: (Engineering (Springer-11647)); (Manufacturing and Surface Engineering, 2365-8223).Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Description: 1 recurso en línea (VIII, 67 páginas) : 10 ilustraciones, 3 ilustraciones a color.ISBN: 9783319923932.Subject: Estadística industrial | Industria -- Proceso de datos | Inteligencia artificial -- IndustriaOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
General aspects and definitions -- Literature Review -- Evolution based methods -- Swarm intelligence based methods -- Other methods -- Case studies and conclusions.
Abstract: This book presents computational and statistical methods used by intelligent systems within the concept of Industry 4.0. The methods include among others evolution-based and swarm intelligence-based methods. Each method is explained in its fundamental aspects, while some notable bibliography is provided for further reading. This book describes each methods' principles and compares them. It is intended for researchers who are new in computational and statistical methods but also to experienced users.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TA345 2019 EB (Browse shelf(Opens below)) Acceso electrónico eBooks24062509
Total holds: 0

General aspects and definitions -- Literature Review -- Evolution based methods -- Swarm intelligence based methods -- Other methods -- Case studies and conclusions.

This book presents computational and statistical methods used by intelligent systems within the concept of Industry 4.0. The methods include among others evolution-based and swarm intelligence-based methods. Each method is explained in its fundamental aspects, while some notable bibliography is provided for further reading. This book describes each methods' principles and compares them. It is intended for researchers who are new in computational and statistical methods but also to experienced users.

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