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Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
Loot Price: R3,313
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Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
Series: Advanced Research in Reliability and System Assurance Engineering
Expected to ship within 12 - 17 working days
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The text discusses the latest data-driven, physics-based, and
hybrid approaches employed in each stage of industrial prognostics
and reliability estimation. It will be a useful text for senior
undergraduate, graduate students, and academic researchers in areas
such as industrial and production engineering, electrical
engineering, and computer science. The book Discusses basic as well
as advance research in the field of prognostics. Explores
integration of data collection, fault detection, degradation
modeling and reliability prediction in one volume. Covers
prognostics and health management (PHM) of engineering systems.
Discusses latest approaches in the field of prognostics based on
machine learning. The text deals with tools and techniques used to
predict/ extrapolate/ forecast the process behavior, based on
current health state assessment and future operating conditions
with the help of Machine learning. It will serve as a useful
reference text for senior undergraduate, graduate students, and
academic researchers in areas such as industrial and production
engineering, manufacturing science, electrical engineering, and
computer science.
General
Imprint: |
Taylor & Francis
|
Country of origin: |
United Kingdom |
Series: |
Advanced Research in Reliability and System Assurance Engineering |
Release date: |
September 2023 |
First published: |
2024 |
Editors: |
Gunjan Soni
• Om Prakash Yadav
• Gaurav Kumar Badhotiya
• Mangey Ram
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Dimensions: |
234 x 156mm (L x W) |
Pages: |
246 |
ISBN-13: |
978-1-03-205436-0 |
Categories: |
Books
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LSN: |
1-03-205436-0 |
Barcode: |
9781032054360 |
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