Capturing Connectivity and Causality in Complex Industrial Processes (Record no. 58779)

000 -LEADER
fixed length control field 03620nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-3-319-05380-6
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112549.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140401s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319053806
-- 978-3-319-05380-6
082 04 - CLASSIFICATION NUMBER
Call Number 620
100 1# - AUTHOR NAME
Author Yang, Fan.
245 10 - TITLE STATEMENT
Title Capturing Connectivity and Causality in Complex Industrial Processes
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 91 p. 54 illus., 24 illus. in color.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Applied Sciences and Technology,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Examples of Applications for Connectivity and Causality Analysis -- Description of Connectivity and Causality -- Capturing Connectivity and Causality from Process Knowledge -- Capturing Causality from Process Data -- Case Studies.
520 ## - SUMMARY, ETC.
Summary, etc This brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways: �      from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and �      from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian networks can be used to identify pair-wise relationships and network topology. These methods rely on the notion of information fusion whereby process operating data is combined with qualitative process knowledge, to give a holistic picture of the system.
700 1# - AUTHOR 2
Author 2 Duan, Ping.
700 1# - AUTHOR 2
Author 2 Shah, Sirish L.
700 1# - AUTHOR 2
Author 2 Chen, Tongwen.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-05380-6
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
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-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2014.
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-- text
-- txt
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-- computer
-- c
-- rdamedia
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-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Chemical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical models.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Complexity, Computational.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
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-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Complexity.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical Modeling and Industrial Mathematics.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Industrial Chemistry/Chemical Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-530X
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-- ZDB-2-ENG

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