Machine learning and knowledge discovery for engineering systems health management / editors, Ashok N. Srivastava and Jiawei Han.

Includes bibliographical references and index.

'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.

'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.