Statistical process monitoring using advanced data-driven and deep learning approaches : (Record no. 2942)

MARC details
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fixed length control field 02402nam a22003017a 4500
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control field 20220613150708.0
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780128193655
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Classification number TS156.8
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Title Statistical process monitoring using advanced data-driven and deep learning approaches :
Remainder of title theory and practical applications /
Statement of responsibility, etc. Fouzi Harrou; Ying Sun; Amanda S Hering; Muddu Madakyaru; Abdelkader Dairi
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Amsterdam, Netherland :
Name of producer, publisher, distributor, manufacturer Elsevier,
Date of production, publication, distribution, manufacture, or copyright notice [2021]
300 ## - PHYSICAL DESCRIPTION
Extent xii, 315 pages
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500 ## - GENERAL NOTE
General note Includes bibliography
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-- 1. Introduction 2. Linear Latent Variable Regression (LVR)-Based Process Monitoring 3. Fault Isolation 4. Nonlinear latent variable regression methods 5. Multiscale latent variable regression-based process monitoring methods 6. Unsupervised deep learning-based process monitoring methods 7. Unsupervised recurrent deep learning schemes for process monitoring 8. Case studies 9. Conclusions and future perspectives
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-- Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches - such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches - to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Process control
General subdivision Statistical methods.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Multivariate analysis
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Harrou, Fouzi
Relator term Co-author
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Sun, Ying
Relator term Co-author
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hering, Amanda S.
Relator term Co-author
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Madakyaru, Muddu
Relator term Co-author
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Dairi, Abdelkader
Relator term Co-author
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Inventory number Total Checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Library of Congress Classification     Harare Institute of Technology Main Library Harare Institute of Technology Main Library General Collection 23/05/2022 Donation : Book Aid International 3859/D   TS156.8 STA BK002655 22/07/2024 1 13/06/2022 Books