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Machine learning and knowledge disco...
~
Srivastava, Ashok N. (1969-)
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Machine learning and knowledge discovery for engineering systems health management
Record Type:
Electronic resources : Monograph/item
Title/Author:
Machine learning and knowledge discovery for engineering systems health management/ edited by Ashok N. Srivastava, Jiawei Han.
other author:
Srivastava, Ashok N.
Published:
Boca Raton, FL :CRC Press, : ©2011.,
Description:
1 online resource (xxxvii, 464 p.) :ill.
[NT 15003449]:
Section 1. Data-driven methods for systems health management -- section 2. Physics-based methods for systems health management -- section 3. Applications.
Subject:
System failures (Engineering) - Prevention -
Online resource:
http://www.crcnetbase.com/doi/book/10.1201/b11580
ISBN:
9781439841792 (electronic bk.)
Machine learning and knowledge discovery for engineering systems health management
Machine learning and knowledge discovery for engineering systems health management
[electronic resource] /edited by Ashok N. Srivastava, Jiawei Han. - Boca Raton, FL :CRC Press,©2011. - 1 online resource (xxxvii, 464 p.) :ill. - Chapman & Hall/CRC data mining and knowledge discovery series. - Chapman & Hall/CRC data mining and knowledge discovery series..
Includes bibliographical references and index.
Section 1. Data-driven methods for systems health management -- section 2. Physics-based methods for systems health management -- section 3. Applications.
"Systems health is a broad multidisciplinary field of study that generates huge amounts of data and thus is an extremely appropriate forum in which to utilize machine learning and knowledge discovery techniques. This book explores the use of machine learning and knowledge discovery in systems health research. It covers data mining and text mining algorithms, anomaly detection, diagnostic and prognostic systems, and applications to engineering systems. Featuring contributions from leading experts, the book is the first to explore this emerging research area"--Provided by publisher.
ISBN: 9781439841792 (electronic bk.)Subjects--Topical Terms:
2090024
System failures (Engineering)
--Prevention
LC Class. No.: TA169.5 / .M33 2011
Dewey Class. No.: 620/.00452
Machine learning and knowledge discovery for engineering systems health management
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Machine learning and knowledge discovery for engineering systems health management
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edited by Ashok N. Srivastava, Jiawei Han.
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Boca Raton, FL :
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CRC Press,
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©2011.
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1 online resource (xxxvii, 464 p.) :
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ill.
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Chapman & Hall/CRC data mining and knowledge discovery series
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Includes bibliographical references and index.
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Section 1. Data-driven methods for systems health management -- section 2. Physics-based methods for systems health management -- section 3. Applications.
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"Systems health is a broad multidisciplinary field of study that generates huge amounts of data and thus is an extremely appropriate forum in which to utilize machine learning and knowledge discovery techniques. This book explores the use of machine learning and knowledge discovery in systems health research. It covers data mining and text mining algorithms, anomaly detection, diagnostic and prognostic systems, and applications to engineering systems. Featuring contributions from leading experts, the book is the first to explore this emerging research area"--Provided by publisher.
520
$a
"This book explores the development of state-of-the-art tools and techniques that can be used to automatically detect, diagnose, and in some cases, predict the effects of adverse events in an engineered system on its ultimate performance. This gives rise to the field Systems Health Management, in which methods are developed with the express purpose of monitoring the condition, or 'state of health' of a complex system, diagnosing faults, and estimating the remaining useful life of the system"--Provided by publisher.
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Print version record.
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System failures (Engineering)
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Prevention
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Srivastava, Ashok N.
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(Ashok Narain),
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1969-
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Han, Jiawei.
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http://www.crcnetbase.com/doi/book/10.1201/b11580
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W9251723
電子資源
11.線上閱覽_V
電子書
EB TA169.5 .M33 2011
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1 records • Pages 1 •
1
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