Ashok N. (Hrsg.) Srivastava

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Buch

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--

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Produktdetails

Weitere Autoren: Han, Jiawei (Hrsg.)

ISBN: 978-1-4398-4178-5
EAN: 9781439841785
Produktnummer: 23094997
Verlag: Taylor and Francis
Sprache: Englisch
Erscheinungsjahr: 2011
Seitenangabe: 502 S.
Masse: H23.4 cm x B15.6 cm 1'090 g
Abbildungen: Farb., s/w. Abb.
Gewicht: 1090

Über den Autor

Ashok N. Srivastava is the Principal Scientist for Data Mining and Systems Health Management at NASA. Dr. Srivastava has received many awards, including the IEEE Computer Society Technical Achievement Award, the NASA Exceptional Achievement Medal, NASA Group Achievement Awards, the IBM Golden Circle Award, and a U.S. Department of Education Merit Fellowship. His current research focuses on the development of data mining algorithms for anomaly detection in massive data streams, kernel methods in machine learning, and text mining algorithms.Jiawei Han is an Abel Bliss Professor of Computer Science at the University of Illinois. He is also the Director of the Information Network Academic Research Center, which is supported by the U.S. Army Research Lab. A fellow of ACM and IEEE, Dr. Han has received numerous honors, including IEEE W. Wallace McDowell Award, IEEE Computer Society Technical Achievement Award, ACM SIGKDD Innovation Award, IBM Faculty awards, and HP Innovation awards. His research interests include data mining, information network analysis, and database systems.