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Quo vadis artificial intelligence?
The study of artificial intelligence (AI) has been a continuous endeavor of scientists and
engineers for over 65 years. The simple contention is that human-created machines can do …
engineers for over 65 years. The simple contention is that human-created machines can do …
Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
State of charge estimation for lithium-ion batteries using model-based and data-driven methods: A review
Lithium-ion battery is an appropriate choice for electric vehicle (EV) due to its promising
features of high voltage, high energy density, low self-discharge and long lifecycles. The …
features of high voltage, high energy density, low self-discharge and long lifecycles. The …
[HTML][HTML] Applications of machine learning methods for engineering risk assessment–A review
The purpose of this article is to present a structured review of publications utilizing machine
learning methods to aid in engineering risk assessment. A keyword search is performed to …
learning methods to aid in engineering risk assessment. A keyword search is performed to …
Deep learning and its applications to machine health monitoring
Abstract Since 2006, deep learning (DL) has become a rapidly growing research direction,
redefining state-of-the-art performances in a wide range of areas such as object recognition …
redefining state-of-the-art performances in a wide range of areas such as object recognition …
A new dynamic model and transfer learning based intelligent fault diagnosis framework for rolling element bearings race faults: Solving the small sample problem
Y Dong, Y Li, H Zheng, R Wang, M Xu - ISA transactions, 2022 - Elsevier
Intelligent fault diagnosis of rolling element bearings gains increasing attention in recent
years due to the promising development of artificial intelligent technology. Many intelligent …
years due to the promising development of artificial intelligent technology. Many intelligent …
Machine health monitoring using local feature-based gated recurrent unit networks
In modern industries, machine health monitoring systems (MHMS) have been applied wildly
with the goal of realizing predictive maintenance including failures tracking, downtime …
with the goal of realizing predictive maintenance including failures tracking, downtime …
Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming
C Ning, F You - Computers & Chemical Engineering, 2019 - Elsevier
This paper reviews recent advances in the field of optimization under uncertainty via a
modern data lens, highlights key research challenges and promise of data-driven …
modern data lens, highlights key research challenges and promise of data-driven …
Learning to monitor machine health with convolutional bi-directional LSTM networks
In modern manufacturing systems and industries, more and more research efforts have been
made in develo** effective machine health monitoring systems. Among various machine …
made in develo** effective machine health monitoring systems. Among various machine …
Deep model based domain adaptation for fault diagnosis
In recent years, machine learning techniques have been widely used to solve many
problems for fault diagnosis. However, in many real-world fault diagnosis applications, the …
problems for fault diagnosis. However, in many real-world fault diagnosis applications, the …