Machine learning and knowledge discovery for engineering systems health management /
General Material Designation
[Book]
First Statement of Responsibility
edited by Ashok N. Srivastava, Jiawei Han
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Boca Raton, FL :
Name of Publisher, Distributor, etc.
CRC Press,
Date of Publication, Distribution, etc.
c2012
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xxxvii, 464 p. :
Other Physical Details
ill. ;
Dimensions
24 cm
SERIES
Series Title
Chapman & Hall/CRC data mining and knowledge discovery series
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index
SUMMARY OR ABSTRACT
Text of Note
"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
Text of Note
"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
Text of Note
"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
Text of Note
"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
TOPICAL NAME USED AS SUBJECT
Machine learning
System failures (Engineering)-- Prevention-- Data processing