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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.Â
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.
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 second
edition has been fully revised and expanded with new content on
swarm intelligence, deep learning, fuzzy data analysis, and
discrete decision graphs. 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.
This clearly-structured, classroom-tested textbook/reference
presents a methodical introduction to the field of CI. Providing an
authoritative insight into all that is necessary for the successful
application of CI methods, the book describes fundamental concepts
and their practical implementations, and explains the theoretical
background underpinning proposed solutions to common problems. Only
a basic knowledge of mathematics is required. Features: provides
electronic supplementary material at an associated website,
including module descriptions, lecture slides, exercises with
solutions, and software tools; contains numerous examples and
definitions throughout the text; presents self-contained
discussions on artificial neural networks, evolutionary algorithms,
fuzzy systems and Bayesian networks; covers the latest approaches,
including ant colony optimization and probabilistic graphical
models; written by a team of highly-regarded experts in CI, with
extensive experience in both academia and industry.
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.
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Computational Intelligence - Eine methodische Einfuhrung in Kunstliche Neuronale Netze, Evolutionare Algorithmen, Fuzzy-Systeme und Bayes-Netze (German, Paperback, 2., uberarb. und erw. Aufl. 2015)
Rudolf Kruse, Christian Borgelt, Christian Braune, Frank Klawonn, Christian Moewes, …
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R2,030
Discovery Miles 20 300
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Ships in 10 - 15 working days
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Die Autoren behandeln umfassend zentrale Themen der Informatik von
Kunstlichen Neuronalen Netzen, uber Evolutionare Algorithmen bis
hin zu Fuzzy-Systemen und Bayes-Netzen. Denn: Der Anwendungsbereich
"Computational Intelligence" erlangt durch viele erfolgreiche
industrielle Produkte immer mehr an Bedeutung. Dieses Buch
behandelt die zentralen Techniken dieses Gebiets und bettet sie in
ein didaktisches Konzept ein, welches sich gezielt an Studierende
und Lehrende der Informatik wendet. Fur die vorliegende 2. Auflage
des Buches wurden alle Themenbereiche uberarbeitet, aktualisiert
und zum Teil erweitert. Zusatzmaterialen wie Aufgaben, Loesungen
und Foliensatze fur Vorlesungen sowie Beispiele aus der
industriellen Anwendung betonen den praktischen Charakter des
Buches.
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