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CRC Press Machine Learning for Engineering Systems Health Management

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Description

Explore the intersection of machine learning and systems health management with this comprehensive volume from CRC Press. This book provides state-of-the-art tools and techniques designed for the automatic detection, diagnosis, and prediction of adverse events within engineered systems. As the first volume to combine these two specific fields, it offers a unique perspective for professionals and students. The content is organized into three distinct parts, guiding readers through the fundamental algorithms and methods used in both physics-based and data-driven approaches. By integrating these methodologies, the book helps address the complex requirements of modern systems health management. Featuring contributions from leading authorities on the subject, this text serves as a vital resource for understanding how data mining and knowledge discovery can be applied to maintain the integrity and performance of engineered systems. Whether you are studying databases or advanced computing, this book provides the technical foundation needed to navigate the evolving landscape of engineering health management.

Key Features

Combines machine learning and systems health management into one unified resource for the first time.

Provides advanced techniques for automatically detecting and diagnosing adverse events in engineered systems.

Covers both physics-based and data-driven approaches to address complex health management needs.

Includes expert contributions from many top authorities in the field of data mining and knowledge discovery.

Organized into three logical parts to explain fundamental algorithms and practical methods effectively.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
16 November 2011
Listed Since
15 February 2010

Barcode

No barcode data available

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