Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
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
September 2023, ca. 246 Seiten, Advanced Research in Reliability and System Assurance Engineering, Englisch
Taylor and Francis
978-1-03-205436-0
Taylor and Francis
978-1-03-205436-0

