Machine learning in medical applications: A review of state-of-the-art methods
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …
complex challenges in recent years in various application areas, such as medical, financial …
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
Machinery prognostics is one of the major tasks in condition based maintenance (CBM),
which aims to predict the remaining useful life (RUL) of machinery based on condition …
which aims to predict the remaining useful life (RUL) of machinery based on condition …
A recurrent neural network based health indicator for remaining useful life prediction of bearings
In data-driven prognostic methods, prediction accuracy of bearing remaining useful life
(RUL) mainly depends on the performance of bearing health indicators, which are usually …
(RUL) mainly depends on the performance of bearing health indicators, which are usually …
[BOOK][B] The illustrated wavelet transform handbook: introductory theory and applications in science, engineering, medicine and finance
PS Addison - 2017 - taylorfrancis.com
This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and
Applications in Science, Engineering, Medicine and Finance has been fully updated and …
Applications in Science, Engineering, Medicine and Finance has been fully updated and …
A comparative study on machine learning algorithms for smart manufacturing: tool wear prediction using random forests
Manufacturers have faced an increasing need for the development of predictive models that
predict mechanical failures and the remaining useful life (RUL) of manufacturing systems or …
predict mechanical failures and the remaining useful life (RUL) of manufacturing systems or …
Deep transfer learning based on sparse autoencoder for remaining useful life prediction of tool in manufacturing
Deep learning with ability to feature learning and nonlinear function approximation has
shown its effectiveness for machine fault prediction. While, how to transfer a deep network …
shown its effectiveness for machine fault prediction. While, how to transfer a deep network …
[HTML][HTML] Tool condition monitoring techniques in milling process—A review
The most important improvement in metal the cutting industry is the continuous utilization of
cutting tools and tool condition monitoring system. In the metal cutting process, the tool …
cutting tools and tool condition monitoring system. In the metal cutting process, the tool …
Remaining useful life prediction based on a double-convolutional neural network architecture
Remaining useful life (RUL) prediction has been increasingly considered in many industrial
fields for the reliability and safety of their systems. As a data analysis tool of deep learning …
fields for the reliability and safety of their systems. As a data analysis tool of deep learning …
An optimized XGBoost method for predicting reservoir porosity using petrophysical logs
S Pan, Z Zheng, Z Guo, H Luo - Journal of Petroleum Science and …, 2022 - Elsevier
To overcome the deficiencies of current porosity prediction methods, the XGBoost algorithm
is introduced to construct a model for porosity prediction, and the obtained model is …
is introduced to construct a model for porosity prediction, and the obtained model is …
Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit
Abstract Remaining Useful Life (RUL) estimation is a fundamental task in the prognostic and
health management (PHM) of industrial equipment and systems. To this end, we propose a …
health management (PHM) of industrial equipment and systems. To this end, we propose a …