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Remaining useful life prediction based on spatiotemporal autoencoder
Remaining Useful Life (RUL) prediction has received a lot of attention as the core of prognostics and health management (PHM) technology. Deep...
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Capsule Network Based on Double-layer Attention Mechanism and Multi-scale Feature Extraction for Remaining Life Prediction
The era of big data provides a platform for high-precision RUL prediction, but the existing RUL prediction methods, which effectively extract key...
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Evolutionary Optimization of Convolutional Extreme Learning Machine for Remaining Useful Life Prediction
Remaining useful life (RUL) prediction is a key enabler for making optimal maintenance strategies. Data-driven approaches, especially employing...
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A transformer with layer-cross decoding for remaining useful life prediction
Remaining useful life (RUL) prediction is critical for industrial equipment status detection, and the accurate prediction results provide...
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Aero-engine remaining useful life prediction based on a long-term channel self-attention network
The accurate prediction of remaining useful life (RUL) is conducive to reducing equipment failure rates and maintenance costs. As the long-term...
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Prediction of Remaining Life of City Gas Pipelines Based on Decision Tree Classification Algorithm
City gas pipelines play a very important role in ensuring urban energy supply, but there is a problem that the remaining life of pipelines is not...
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Prediction of fault evolution and remaining useful life for rolling bearings with spalling fatigue using digital twin technology
AbstractQuantifying fault severity is a critical part of rolling bearing health management. There are numerous methods for evaluating the severity of...
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A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries
Accurately predicting the Remaining Useful Life (RUL) of lithium-ion batteries is crucial for battery management systems. Deep learning-based methods...
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A novel spatio-temporal hybrid neural network for remaining useful life prediction
Remaining useful life (RUL) prediction is a crucial mission for the prognostic and health management (PHM) of machinery equipment in modern industry....
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Deep learning models for human age prediction to prevent, treat and extend life expectancy: DCPV taxonomy
The implementation of Deep Learning (DL) Prediction techniques for Human Age Prediction (HAP) has been widely researched and studied to prevent,...
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A denoising semi-supervised deep learning model for remaining useful life prediction of turbofan engine degradation
Remaining useful life (RUL) prediction is significant for reliability analysis and the reduction of maintenance costs for turbofan engine systems....
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Enhancing EV lithium-ion battery management: automated machine learning for early remaining useful life prediction with innovative multi-health indicators
Addressing the need for multiple health indicators is critical to improving prediction accuracy and reducing the limitation of reliance on a single...
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Mechanical element’s remaining useful life prediction using a hybrid approach of CNN and LSTM
For the safety and reliability of the system, Remaining Useful Life (RUL) prediction is considered in many industries. The traditional machine...
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A hybrid-driven remaining useful life prediction method combining asymmetric dual-channel autoencoder and nonlinear Wiener process
Remaining Useful Life (RUL) prediction is an essential aspect of Prognostics and Health Management (PHM), facilitating the assessment of mechanical...
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Privacy-Preserving Machine Learning in Life Insurance Risk Prediction
The application of machine learning to insurance risk prediction requires learning from sensitive data. This raises multiple ethical and legal...
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Degradation Modelling and Remaining Useful Life Prediction Methods Based on Time Series Generative Prediction Networks
Currently, in the field of prediction and health management, there is a proliferation of deep learning approaches to degradation modeling and...
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Wasserstein distance based multi-scale adversarial domain adaptation method for remaining useful life prediction
Accurate remaining useful life (RUL) prediction can formulate timely maintenance strategies for mechanical equipment and reduce the costs of...
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Emotion Prediction in Real-Life Scenarios: On the Way to the BIRAFFE3 Dataset
Despite over 20 years of research in affective computing, emotion prediction models that would be useful in real-life out-of-the-lab scenarios such...
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Remaining Useful Life Prediction of Control Moment Gyro in Orbiting Spacecraft Based on Variational Autoencoder
For the telemetry data generated by the key components of spacecraft during the orbital operation contain a lot of degradation information, and these...
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VisPro: a prognostic SqueezeNet and non-stationary Gaussian process approach for remaining useful life prediction with uncertainty quantification
Rotating machinery is essential to modern life, from power generation to transportation and a host of other industrial applications. Since such...
