Machine Learning and Knowledge Discovery for Engineering Systems Health Management PDF
Edited by Ashok N. Srivastava, Jiawei Han
Part of the Chapman & Hall/CRC Data Mining and Knowledge Discovery Series series
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Description
This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system.
It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability.
Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.
Information
-
Download - Immediately Available
- Format:PDF
- Pages:502 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:19/04/2016
- Category:
- ISBN:9781439841792
Information
-
Download - Immediately Available
- Format:PDF
- Pages:502 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:19/04/2016
- Category:
- ISBN:9781439841792
