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Intelligent Prognostics for Engineering Systems with Machine Learning Techniques.
・ISBN 978-1-032-56297-1 paper GB£ 62.99
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| 著者・編者 | Soni, Gunjan / Yadav, Om Prakash / Badhotiya, Gaurav Kumar / Ram, Mangey (eds.), |
|---|---|
| シリーズ | (Advanced Research in Reliability and System Assurance Engineering) |
| 出版社 | (CRC Press, UK) |
| 出版年月 | 2024 |
| ページ数 | 246 pp. |
| 言語 | ENG |
| ニュース番号 | <A03-79146> |
解説
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.