Pengyu Song
Orcid: 0009-0006-4522-1386
According to our database1,
Pengyu Song
authored at least 16 papers
between 2020 and 2024.
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Bibliography
2024
Hybrid Probabilistic Slow Feature Analysis of Continuous and Binary Data for Dynamic Process Monitoring.
IEEE Trans. Syst. Man Cybern. Syst., December, 2024
Structure Feature Extraction for Hierarchical Alarm Flood Classification and Alarm Prediction.
IEEE Trans Autom. Sci. Eng., July, 2024
Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes.
IEEE Trans. Neural Networks Learn. Syst., March, 2024
IEEE Trans. Neural Networks Learn. Syst., March, 2024
Multi-scale self-supervised representation learning with temporal alignment for multi-rate time series modeling.
Pattern Recognit., January, 2024
Multimodal Decoupled Representation With Compatibility Learning for Explicit Nonstationary Process Monitoring.
IEEE Trans. Ind. Electron., 2024
Towards consensual representation: Model-agnostic knowledge extraction for dual heterogeneous federated fault diagnosis.
Neural Networks, 2024
Facing spatiotemporal heterogeneity: A unified federated continual learning framework with self-challenge rehearsal for industrial monitoring tasks.
Knowl. Based Syst., 2024
Fusing consensus knowledge: A federated learning method for fault diagnosis via privacy-preserving reference under domain shift.
Inf. Fusion, 2024
Optimization of Machine Vision Dynamic Monitoring System Based on Deep Learning Algorithms.
Proceedings of the 2024 4th International Conference on Internet of Things and Machine Learning, 2024
2023
MPGE and RootRank: A sufficient root cause characterization and quantification framework for industrial process faults.
Neural Networks, April, 2023
Spatiotemporal Multiscale Correlation Embedding With Process Variable Reorder for Industrial Soft Sensing.
IEEE Trans. Instrum. Meas., 2023
2022
Sparse and Time-Varying Predictive Relation Extraction for Root Cause Quantification of Nonstationary Process Faults.
IEEE Trans. Instrum. Meas., 2022
SFNet: A slow feature extraction network for parallel linear and nonlinear dynamic process monitoring.
Neurocomputing, 2022
2020
Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting.
CoRR, 2020
Multivariate Time Series Forecasting Based on Causal Inference with Transfer Entropy and Graph Neural Network.
CoRR, 2020