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Applications of Artificial Intelligence Techniques in Industry 4.0 / by Aydin Azizi.

Springer Nature - Springer Engineering eBooks 2019 English International Available online

Springer Nature - Springer Engineering eBooks 2019 English International
Format:
Book
Author/Creator:
Azizi, Aydin, author.
Contributor:
SpringerLink (Online service)
Series:
Engineering (Springer-11647)
SpringerBriefs in applied sciences and technology 2191-530X
SpringerBriefs in Applied Sciences and Technology, 2191-530X
Language:
English
Subjects (All):
Electrical engineering.
Artificial intelligence.
Engineering economy.
Communications Engineering, Networks.
Artificial Intelligence.
Engineering Economics, Organization, Logistics, Marketing.
Local Subjects:
Communications Engineering, Networks.
Artificial Intelligence.
Engineering Economics, Organization, Logistics, Marketing.
Physical Description:
1 online resource (XII, 61 pages) : 50 illustrations, 34 illustrations in color.
Edition:
First edition 2019.
Contained In:
Springer eBooks
Place of Publication:
Singapore : Springer Singapore : Imprint: Springer, 2019.
System Details:
text file PDF
Summary:
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.
Contents:
Introduction
Modern Manufacturing
RFID Network Planning
Hybrid Artificial Intelligence Optimization Technique
Implementation.
Other Format:
Printed edition:
ISBN:
978-981-13-2640-0
9789811326400
OCLC:
1054627590
Access Restriction:
Restricted for use by site license.

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