A review on the application of deep learning in system health management

S Khan, T Yairi - Mechanical Systems and Signal Processing, 2018 - Elsevier
Given the advancements in modern technological capabilities, having an integrated health
management and diagnostic strategy becomes an important part of a system's operational …

A comprehensive survey of prognostics and health management based on deep learning for autonomous ships

AL Ellefsen, V Æsøy, S Ushakov… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The maritime industry widely expects to have autonomous and semiautonomous ships
(autoships) in the near future. In order to operate and maintain complex and integrated …

A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment

Z Li, J Li, Y Wang, K Wang - The International Journal of Advanced …, 2019 - Springer
Anomaly in mechanical systems may cause equipment to break down with serious safety,
environment, and economic impact. Since many mechanical equipment usually operates …

A deep active survival analysis approach for precision treatment recommendations: Application of prostate cancer

MZ Nezhad, N Sadati, K Yang, D Zhu - Expert Systems with Applications, 2019 - Elsevier
Survival analysis has been developed and applied in the number of areas including
manufacturing, finance, economics and healthcare. In healthcare domain, usually clinical …

Prediction of conversion to Alzheimer's disease using deep survival analysis of MRI images

T Nakagawa, M Ishida, J Naito, A Nagai… - Brain …, 2020 - academic.oup.com
The prediction of the conversion of healthy individuals and those with mild cognitive
impairment to the status of active Alzheimer's disease is a challenging task. Recently, a …

Evaluating feature selection and anomaly detection methods of hard drive failure prediction

Q Yang, X Jia, X Li, J Feng, W Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
As vast amounts of data are saved, hard drive failure prediction is critical to reducing the cost
of data loss and backup. Most existing studies used to detect the anomalous status of a hard …

Transfer learning for Prognostics and health Management (PHM) of marine Air Compressors

M Gribbestad, MU Hassan, IA Hameed - Journal of Marine Science and …, 2021 - mdpi.com
Prognostics is an engineering discipline focused on predicting the time at which a system or
a component will no longer perform its intended function. Due to the requirements of system …

Deep learning for survival outcomes

JA Steingrimsson, S Morrison - Statistics in medicine, 2020 - Wiley Online Library
Deep learning is a class of machine learning algorithms that are popular for building risk
prediction models. When observations are censored, the outcomes are only partially …

Deep semisupervised multitask learning model and its interpretability for survival analysis

S Chi, Y Tian, F Wang, Y Wang… - IEEE journal of …, 2021 - ieeexplore.ieee.org
Survival analysis is a commonly used method in the medical field to analyze and predict the
time of events. In medicine, this approach plays a key role in determining the course of …

A systematic review for switchgear asset management in power grids: condition monitoring, health assessment, and maintenance strategy

N Zhou, Y Xu, S Cho, CT Wee - IEEE Transactions on Power …, 2023 - ieeexplore.ieee.org
Asset management process and techniques can improve the cost-efficiency, balance the
cost and risk, and prolong the service life of the aging switchgears in power grids, which …