Fault detection and diagnosis using combined autoencoder and long short-term memory network
Fault detection and diagnosis is one of the most critical components of preventing accidents
and ensuring the system safety of industrial processes. In this paper, we propose an …
and ensuring the system safety of industrial processes. In this paper, we propose an …
A comprehensive survey on rare event prediction
Rare event prediction involves identifying and forecasting events with a low probability using
machine learning and data analysis. Due to the imbalanced data distributions, where the …
machine learning and data analysis. Due to the imbalanced data distributions, where the …
Unsupervised anomaly detection in IoT systems for smart cities
Anomaly detection is critical in the Internet of Things (IoT) systems due to its wide
applications for building smart cities, such as quality control in manufacturing, intrusion …
applications for building smart cities, such as quality control in manufacturing, intrusion …
Stacking-based ensemble learning for remaining useful life estimation
Excessive and untimely maintenance prompts economic losses and unnecessary workload.
Therefore, predictive maintenance models are developed to estimate the right time for …
Therefore, predictive maintenance models are developed to estimate the right time for …
[PDF][PDF] Understanding deep learning: Application in rare event prediction
C Ranjan - … Learning; Connaissance Publishing: Atlanta, GA, USA, 2020 - researchgate.net
Deep learning is an art. But it has some boundaries. Learning the boundaries is essential to
develop working solutions and, ultimately, push them for novel creations. For example …
develop working solutions and, ultimately, push them for novel creations. For example …
[HTML][HTML] LSTM-based framework with metaheuristic optimizer for manufacturing process monitoring
CL Yang, AA Yilma, H Sutrisno… - Alexandria Engineering …, 2023 - Elsevier
Quick process shift detection and lower out-of-control run length are essential for monitoring
the production process, especially in modern smart manufacturing. Specifically, the out-of …
the production process, especially in modern smart manufacturing. Specifically, the out-of …
A Systematic Review of Rare Events Detection Across Modalities using Machine Learning and Deep Learning
Rare event detection (RED) involves the identification and detection of events characterized
by low frequency of occurrences, but of high importance or impact. This paper presents a …
by low frequency of occurrences, but of high importance or impact. This paper presents a …
MMA: metadata supported multi-variate attention for onset detection and prediction
Deep learning has been applied successfully in sequence understanding and translation
problems, especially in univariate, unimodal contexts, where large number of supervision …
problems, especially in univariate, unimodal contexts, where large number of supervision …
Data augmentation for bearing fault detection with a light weight CNN
JW Oh, J Jeong - Procedia computer science, 2020 - Elsevier
Bearings are vital part of rotary machines. A failure of bearing has a negative impact on
schedules, production operation and even human casualties. Therefore, in prior achieving …
schedules, production operation and even human casualties. Therefore, in prior achieving …
Training data selection by categorical variables for better rare event prediction in multiple products production line
D Xu, Z Zhang, J Shi - Electronics, 2022 - mdpi.com
Manufacturers are struggling to use data from multiple products production lines to predict
rare events. Improving the quality of training data is a common way to improve the …
rare events. Improving the quality of training data is a common way to improve the …