Nature-Inspired Computing and Optimization (Record no. 79832)

000 -LEADER
fixed length control field 03869nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-3-319-50920-4
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801221604.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 170308s2017 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319509204
-- 978-3-319-50920-4
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
245 10 - TITLE STATEMENT
Title Nature-Inspired Computing and Optimization
Sub Title Theory and Applications /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XXI, 494 p. 191 illus., 43 illus. in color.
490 1# - SERIES STATEMENT
Series statement Modeling and Optimization in Science and Technologies,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 From the content: The Nature of Nature: Why Nature Inspired Algorithms Work -- Improved Bat Algorithm in Noise-Free and Noisy Environments -- Multi-objective Ant Colony Optimisation in Wireless Sensor Networks.le.
520 ## - SUMMARY, ETC.
Summary, etc The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.
700 1# - AUTHOR 2
Author 2 Patnaik, Srikanta.
700 1# - AUTHOR 2
Author 2 Yang, Xin-She.
700 1# - AUTHOR 2
Author 2 Nakamatsu, Kazumi.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-50920-4
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2017.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical optimization.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer simulation.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial Management.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Optimization.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Modelling.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial Management.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2196-7334 ;
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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