Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …
essential layer of safety assurance that could lead to more principled decision making by …
Machine learning applications in minerals processing: A review
JT McCoy, L Auret - Minerals Engineering, 2019 - Elsevier
Abstract Machine learning and artificial intelligence techniques have an ever-increasing
presence and impact on a wide-variety of research and commercial fields. Disappointed by …
presence and impact on a wide-variety of research and commercial fields. Disappointed by …
Machine learning pipeline for battery state-of-health estimation
Lithium-ion batteries are ubiquitous in applications ranging from portable electronics to
electric vehicles. Irrespective of the application, reliable real-time estimation of battery state …
electric vehicles. Irrespective of the application, reliable real-time estimation of battery state …
Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology
A Botchkarev - arxiv preprint arxiv:1809.03006, 2018 - arxiv.org
Performance metrics (error measures) are vital components of the evaluation frameworks in
various fields. The intention of this study was to overview of a variety of performance metrics …
various fields. The intention of this study was to overview of a variety of performance metrics …
A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings
Z Pan, Z Meng, Z Chen, W Gao, Y Shi - Mechanical Systems and Signal …, 2020 - Elsevier
Rolling-element bearing is one of the main parts of rotating equipment. In order to avoid the
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
Multiobjective deep belief networks ensemble for remaining useful life estimation in prognostics
In numerous industrial applications where safety, efficiency, and reliability are among
primary concerns, condition-based maintenance (CBM) is often the most effective and …
primary concerns, condition-based maintenance (CBM) is often the most effective and …
[HTML][HTML] Relation between prognostics predictor evaluation metrics and local interpretability SHAP values
Maintenance decisions in domains such as aeronautics are becoming increasingly
dependent on being able to predict the failure of components and systems. When data …
dependent on being able to predict the failure of components and systems. When data …
Monash time series forecasting archive
Many businesses and industries nowadays rely on large quantities of time series data
making time series forecasting an important research area. Global forecasting models that …
making time series forecasting an important research area. Global forecasting models that …
A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelines
The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …
applications. It is of no exception in the area of prognostics and health management (PHM) …
Bidirectional handshaking LSTM for remaining useful life prediction
Unpredictable failures and unscheduled maintenance of physical systems increases
production resources, produces more harmful waste for the environment, and increases …
production resources, produces more harmful waste for the environment, and increases …