Evolutionary Computation Techniques: A Comparative Perspective (Record no. 80544)

000 -LEADER
fixed length control field 03377nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-319-51109-2
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801222231.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 161228s2017 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319511092
-- 978-3-319-51109-2
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Cuevas, Erik.
245 10 - TITLE STATEMENT
Title Evolutionary Computation Techniques: A Comparative Perspective
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XV, 222 p. 74 illus., 33 illus. in color.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Preface -- Introduction -- Multilevel segmentation in digital images -- Multi-Circle detection on images -- Template matching -- Motion estimation -- Photovoltaic cell design -- Parameter identification of induction motors -- White blood cells Detection in images -- Estimation of view transformations in images -- Filter Design.
520 ## - SUMMARY, ETC.
Summary, etc This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.
700 1# - AUTHOR 2
Author 2 Osuna, Valentín.
700 1# - AUTHOR 2
Author 2 Oliva, Diego.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-51109-2
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2017.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-9503 ;
912 ## -
-- ZDB-2-ENG
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-- ZDB-2-SXE

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