Intelligent Prognostics for Engineering Systems with Machine Learning Techniques Hardback
Edited by Gunjan (MNIT, Jaipur, India) Soni, Om Prakash (North Dakota State University, USA.) Yadav, Gaurav Kumar (Graphic Era Uni, Uttarakhand, India.) Badhotiya, Mangey (Graphic Era Uni, India) Ram
Part of the Advanced Research in Reliability and System Assurance Engineering series
Hardback
Description
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 bookDiscusses basic as well as advance research in the field of prognosticsExplores integration of data collection, fault detection, degradation modeling and reliability prediction in one volumeCovers prognostics and health management (PHM) of engineering systemsDiscusses latest approaches in the field of prognostics based on machine learningThe 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.
Information
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Out of stock
- Format:Hardback
- Pages:246 pages, 64 Tables, black and white; 122 Line drawings, black and white; 11 Halftones, black and w
- Publisher:Taylor & Francis Ltd
- Publication Date:22/09/2023
- Category:
- ISBN:9781032054360
Information
-
Out of stock
- Format:Hardback
- Pages:246 pages, 64 Tables, black and white; 122 Line drawings, black and white; 11 Halftones, black and w
- Publisher:Taylor & Francis Ltd
- Publication Date:22/09/2023
- Category:
- ISBN:9781032054360
