A survey of distributed optimization
In distributed optimization of multi-agent systems, agents cooperate to minimize a global
function which is a sum of local objective functions. Motivated by applications including …
function which is a sum of local objective functions. Motivated by applications including …
Smart machining process using machine learning: A review and perspective on machining industry
Abstract The Fourth Industrial Revolution incorporates the digital revolution into the physical
world, creating a new direction in a number of fields, including artificial intelligence, quantum …
world, creating a new direction in a number of fields, including artificial intelligence, quantum …
AGGN: Attention-based glioma grading network with multi-scale feature extraction and multi-modal information fusion
In this paper, a magnetic resonance imaging (MRI) oriented novel attention-based glioma
grading network (AGGN) is proposed. By applying the dual-domain attention mechanism …
grading network (AGGN) is proposed. By applying the dual-domain attention mechanism …
Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression
To solve the problem of the inaccurate prediction on remaining useful life (RUL) for lithium-
ion battery, we proposed an integrated algorithm which combines adaptive unscented …
ion battery, we proposed an integrated algorithm which combines adaptive unscented …
Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network
Accurate estimation of the remaining useful life of lithium-ion batteries is critically important
for electronic devices. In the existing literature, the widely applied model-based approaches …
for electronic devices. In the existing literature, the widely applied model-based approaches …
Real-time monitoring and control of industrial cyberphysical systems: With integrated plant-wide monitoring and control framework
S Yin, JJ Rodriguez-Andina… - IEEE Industrial Electronics …, 2019 - ieeexplore.ieee.org
This article is focused on the realtime monitoring and control aspects of ICPSs. Advanced
approaches and potential challenges are illustrated in the following sections. Especially, an …
approaches and potential challenges are illustrated in the following sections. Especially, an …
A deep learning-based remaining useful life prediction approach for bearings
In industrial applications, nearly half the failures of motors are caused by the degradation of
rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life …
rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life …
A recurrent neural network approach for remaining useful life prediction utilizing a novel trend features construction method
Data-driven methods for remaining useful life (RUL) prediction normally learn features from
a fixed window size of a priori of degradation, which may lead to less accurate prediction …
a fixed window size of a priori of degradation, which may lead to less accurate prediction …
A general end-to-end diagnosis framework for manufacturing systems
The manufacturing sector is envisioned to be heavily influenced by artificial-intelligence-
based technologies with the extraordinary increases in computational power and data …
based technologies with the extraordinary increases in computational power and data …
The interpretive model of manufacturing: a theoretical framework and research agenda for machine learning in manufacturing
Manufacturing is undergoing a paradigmatic shift as it assimilates and is transformed by
machine learning and other cognitive technologies. A new paradigm usually necessitates a …
machine learning and other cognitive technologies. A new paradigm usually necessitates a …