Applications of Artificial Intelligence Techniques in Industry 4.0 (Record no. 76220)

000 -LEADER
fixed length control field 03207nam a22005295i 4500
001 - CONTROL NUMBER
control field 978-981-13-2640-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801214325.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180925s2019 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811326400
-- 978-981-13-2640-0
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
100 1# - AUTHOR NAME
Author Azizi, Aydin.
245 10 - TITLE STATEMENT
Title Applications of Artificial Intelligence Techniques in Industry 4.0
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2019.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XII, 61 p. 50 illus., 34 illus. in color.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Applied Sciences and Technology,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Modern Manufacturing -- RFID Network Planning -- Hybrid Artificial Intelligence Optimization Technique -- Implementation.
520 ## - SUMMARY, ETC.
Summary, etc This book is to presents and evaluates a way of modelling and optimizing nonlinear RFID Network Planning (RNP) problems using artificial intelligence techniques. It uses Artificial Neural Network models (ANN) to bind together the computational artificial intelligence algorithm with knowledge representation an efficient artificial intelligence paradigm to model and optimize RFID networks. This effort leads to proposing a novel artificial intelligence algorithm which has been named hybrid artificial intelligence optimization technique to perform optimization of RNP as a hard learning problem. This hybrid optimization technique consists of two different optimization phases. First phase is optimizing RNP by Redundant Antenna Elimination (RAE) algorithm and the second phase which completes RNP optimization process is Ring Probabilistic Logic Neural Networks (RPLNN). The hybrid paradigm is explored using a flexible manufacturing system (FMS) and the results are compared with well-known evolutionary optimization technique namely Genetic Algorithm (GA) to demonstrate the feasibility of the proposed architecture successfully.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-13-2640-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2019.
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-- txt
-- rdacontent
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Telecommunication.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial Management.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Communications Engineering, Networks.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial Management.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-5318
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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