Adaptive Working Condition Recognition With Clustering-Based Contrastive Learning for Unsupervised Anomaly Detection.
IEEE Trans. Ind. Informatics, October, 2024
A Robust Anomaly Detection Model for Pumps Based on the Spectral Residual With Self-Attention Variational Autoencoder.
IEEE Trans. Ind. Informatics, June, 2024
Remaining Useful Life Prediction Via Interactive Attention-Based Deep Spatio-Temporal Network Fusing Multisource Information.
IEEE Trans. Ind. Electron., 2024
Deep Mixed Domain Generalization Network for Intelligent Fault Diagnosis Under Unseen Conditions.
IEEE Trans. Ind. Electron., 2024
Data-driven predictive maintenance framework considering the multi-source information fusion and uncertainty in remaining useful life prediction.
Knowl. Based Syst., 2024
Deep factor asset pricing with policy guidance based on multi-source heterogeneous information.
Appl. Soft Comput., 2024
Anomaly detection for multivariate times series through the multi-scale convolutional recurrent variational autoencoder.
Expert Syst. Appl., November, 2023
The impact of social media input intensity on reward-based crowdfunding performance: evidence from China.
Electron. Commer. Res., September, 2023
Few-shot fault diagnosis of rotating machinery with two-branch prototypical networks.
J. Intell. Manuf., April, 2023
A composite quantile regression long short-term memory network with group lasso for wind turbine anomaly detection.
J. Ambient Intell. Humaniz. Comput., March, 2023
Class-Imbalance Privacy-Preserving Federated Learning for Decentralized Fault Diagnosis With Biometric Authentication.
IEEE Trans. Ind. Informatics, 2022
Weighted quantile discrepancy-based deep domain adaptation network for intelligent fault diagnosis.
Knowl. Based Syst., 2022
Dissecting click farming on the Taobao platform in China via PU learning and weighted logistic regression.
Electron. Commer. Res., 2022
Tail dependence network of new energy vehicle industry in mainland China.
Ann. Oper. Res., 2022
Non-rechargeable battery remaining useful life prediction with interactive attention sequence to sequence network.
Proceedings of the 20th IEEE International Conference on Industrial Informatics, 2022
QRNN-MIDAS: A novel quantile regression neural network for mixed sampling frequency data.
Neurocomputing, 2021
Which goods are most likely to be subject to click farming? An evidence from the Taobao platform.
Electron. Commer. Res. Appl., 2021
Reverse restricted MIDAS model with application to US interest rate forecasts.
Commun. Stat. Simul. Comput., 2021
A novel (U)MIDAS-SVR model with multi-source market sentiment for forecasting stock returns.
Neural Comput. Appl., 2020
Imbalanced fault diagnosis of rotating machinery via multi-domain feature extraction and cost-sensitive learning.
J. Intell. Manuf., 2020
The impact of soft information extracted from descriptive text on crowdfunding performance.
Electron. Commer. Res. Appl., 2020
Does Google search index really help predicting stock market volatility? Evidence from a modified mixed data sampling model on volatility.
Knowl. Based Syst., 2019
An artificial neural network for mixed frequency data.
Expert Syst. Appl., 2019
A novel UMIDAS-SVQR model with mixed frequency investor sentiment for predicting stock market volatility.
Expert Syst. Appl., 2019
Sampling Lasso quantile regression for large-scale data.
Commun. Stat. Simul. Comput., 2018
Expectile regression neural network model with applications.
Neurocomputing, 2017
Composite quantile regression neural network with applications.
Expert Syst. Appl., 2017
An exponentially weighted quantile regression via SVM with application to estimating multiperiod VaR.
Stat. Methods Appl., 2016
Quantile autoregression neural network model with applications to evaluating value at risk.
Appl. Soft Comput., 2016
Weighted quantile regression via support vector machine.
Expert Syst. Appl., 2015