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Complex systems and their phenomena are ubiquitous as they can be
found in biology, finance, the humanities, management sciences,
medicine, physics and similar fields. For many problems in these
fields, there are no conventional ways to mathematically or
analytically solve them completely at low cost. On the other hand,
nature already solved many optimization problems efficiently.
Computational intelligence attempts to mimic nature-inspired
problem-solving strategies and methods. These strategies can be
used to study, model and analyze complex systems such that it
becomes feasible to handle them. Key areas of computational
intelligence are artificial neural networks, evolutionary
computation and fuzzy systems. As only a few researchers in that
field, Rudolf Kruse has contributed in many important ways to the
understanding, modeling and application of computational
intelligence methods. On occasion of his 60th birthday, a
collection of original papers of leading researchers in the field
of computational intelligence has been collected in this volume.
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.
Complex systems and their phenomena are ubiquitous as they can be
found in biology, finance, the humanities, management sciences,
medicine, physics and similar fields. For many problems in these
fields, there are no conventional ways to mathematically or
analytically solve them completely at low cost. On the other hand,
nature already solved many optimization problems efficiently.
Computational intelligence attempts to mimic nature-inspired
problem-solving strategies and methods. These strategies can be
used to study, model and analyze complex systems such that it
becomes feasible to handle them. Key areas of computational
intelligence are artificial neural networks, evolutionary
computation and fuzzy systems. As only a few researchers in that
field, Rudolf Kruse has contributed in many important ways to the
understanding, modeling and application of computational
intelligence methods. On occasion of his 60th birthday, a
collection of original papers of leading researchers in the field
of computational intelligence has been collected in this volume.
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.
In recent years there has been a growing interest to extend
classical methods for data analysis. The aim is to allow a more
flexible modeling of phenomena such as uncertainty, imprecision or
ignorance. Such extensions of classical probability theory and
statistics are useful in many real-life situations, since
uncertainties in data are not only present in the form of
randomness --- various types of incomplete or subjective
information have to be handled. About twelve years ago the idea of
strengthening the dialogue between the various research communities
in the field of data analysis was born and resulted in the
International Conference Series on Soft Methods in Probability and
Statistics (SMPS). This book gathers contributions presented at the
SMPS'2012 held in Konstanz, Germany. Its aim is to present recent
results illustrating new trends in intelligent data analysis. It
gives a comprehensive overview of current research into the fusion
of soft computing methods with probability and statistics.
Synergies of both fields might improve intelligent data analysis
methods in terms of robustness to noise and applicability to larger
datasets, while being able to efficiently obtain understandable
solutions of real-world problems.
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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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R2,005
Discovery Miles 20 050
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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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