Wentao Mao
Orcid: 0000-0001-5335-9517
According to our database1,
Wentao Mao
authored at least 58 papers
between 2008 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines.
Reliab. Eng. Syst. Saf., February, 2024
Harmony better than uniformity: A new pre-training anomaly detection method with tensor domain adaptation for early fault evaluation.
Eng. Appl. Artif. Intell., January, 2024
SWDAE: A New Degradation State Evaluation Method for Metro Wheels With Interpretable Health Indicator Construction Based on Unsupervised Deep Learning.
IEEE Trans. Instrum. Meas., 2024
2023
An Efficient Two-Stage Surrogate-Assisted Differential Evolution for Expensive Inequality Constrained Optimization.
IEEE Trans. Syst. Man Cybern. Syst., December, 2023
Edge-Cloud Co-Evolutionary Algorithms for Distributed Data-Driven Optimization Problems.
IEEE Trans. Cybern., October, 2023
Robust Interval Prediction of Intermittent Demand for Spare Parts Based on Tensor Optimization.
Sensors, August, 2023
Unsupervised Anomaly Detection for Intermittent Sequences Based on Multi-Granularity Abnormal Pattern Mining.
Entropy, January, 2023
A New Deep Tensor Autoencoder Network for Unsupervised Health Indicator Construction and Degradation State Evaluation of Metro Wheel.
IEEE Trans. Instrum. Meas., 2023
Self-Supervised Deep Tensor Domain-Adversarial Regression Adaptation for Online Remaining Useful Life Prediction Across Machines.
IEEE Trans. Instrum. Meas., 2023
Self-Supervised Deep Domain-Adversarial Regression Adaptation for Online Remaining Useful Life Prediction of Rolling Bearing Under Unknown Working Condition.
IEEE Trans. Ind. Informatics, 2023
IEEE CAA J. Autom. Sinica, 2023
Entropy, 2023
2022
Unsupervised Deep Multitask Anomaly Detection With Robust Alarm Strategy for Online Evaluation of Bearing Early Fault Occurrence.
IEEE Trans. Instrum. Meas., 2022
An Interpretable Deep Transfer Learning-Based Remaining Useful Life Prediction Approach for Bearings With Selective Degradation Knowledge Fusion.
IEEE Trans. Instrum. Meas., 2022
An Adaptive Stochastic Dominant Learning Swarm Optimizer for High-Dimensional Optimization.
IEEE Trans. Cybern., 2022
The Robust Multi-Scale Deep-SVDD Model for Anomaly Online Detection of Rolling Bearings.
Sensors, 2022
Digit. Signal Process., 2022
Research on On-line Data Prediction of Electrical Equipment Based on Wavelet Analysis and Data Fusion.
Proceedings of the IPEC 2022: 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers, Dalian, China, April 14, 2022
2021
A New Structured Domain Adversarial Neural Network for Transfer Fault Diagnosis of Rolling Bearings Under Different Working Conditions.
IEEE Trans. Instrum. Meas., 2021
Construction of Health Indicators for Rotating Machinery Using Deep Transfer Learning With Multiscale Feature Representation.
IEEE Trans. Instrum. Meas., 2021
A New Deep Dual Temporal Domain Adaptation Method for Online Detection of Bearings Early Fault.
Entropy, 2021
Hybrid Particle Swarm and Grey Wolf Optimizer and its application to clustering optimization.
Appl. Soft Comput., 2021
Three-Dimensional Elastodynamic Analysis Employing Partially Discontinuous Boundary Elements.
Algorithms, 2021
Prediction of Bearings Remaining Useful Life Across Working Conditions Based on Transfer Learning and Time Series Clustering.
IEEE Access, 2021
A New Unsupervised Online Early Fault Detection Framework of Rolling Bearings Based on Granular Feature Forecasting.
IEEE Access, 2021
Research on Key Technologies of Large Data Smart Grid Based on Power Grid Operation Simulation.
Proceedings of the 4th International Conference on Information Systems and Computer Aided Education, 2021
2020
Predicting Remaining Useful Life of Rolling Bearings Based on Deep Feature Representation and Transfer Learning.
IEEE Trans. Instrum. Meas., 2020
A New Online Detection Approach for Rolling Bearing Incipient Fault via Self-Adaptive Deep Feature Matching.
IEEE Trans. Instrum. Meas., 2020
Failure prediction of tasks in the cloud at an earlier stage: a solution based on domain information mining.
Computing, 2020
Improved Laplacian Biogeography-Based Optimization Algorithm and Its Application to QAP.
Complex., 2020
2019
ν-Support Vector Regression Model Based on Gauss-Laplace Mixture Noise Characteristic for Wind Speed Prediction.
Entropy, 2019
Lévy Flight Shuffle Frog Leaping Algorithm Based on Differential Perturbation and Quasi-Newton Search.
IEEE Access, 2019
Imbalanced Fault Diagnosis of Rolling Bearing Based on Generative Adversarial Network: A Comparative Study.
IEEE Access, 2019
2018
Online Bearing Fault Diagnosis using Support Vector Machine and Stacked Auto-Encoder.
Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018
Proceedings of the 2018 Annual American Control Conference, 2018
2017
An ELM-based model with sparse-weighting strategy for sequential data imbalance problem.
Int. J. Mach. Learn. Cybern., 2017
Online sequential prediction of imbalance data with two-stage hybrid strategy by extreme learning machine.
Neurocomputing, 2017
Online Extreme Learning Machine with Hybrid Sampling Strategy for Sequential Imbalanced Data.
Cogn. Comput., 2017
2016
基于主曲线的不均衡在线贯序极限学习机研究 (Imbalanced Online Sequential Extreme Learning Machine Based on Principal Curve).
计算机科学, 2016
2015
Online sequential classification of imbalanced data by combining extreme learning machine and improved SMOTE algorithm.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015
2014
Uncertainty evaluation and model selection of extreme learning machine based on Riemannian metric.
Neural Comput. Appl., 2014
Leave-one-out cross-validation-based model selection for multi-input multi-output support vector machine.
Neural Comput. Appl., 2014
A fast and robust model selection algorithm for multi-input multi-output support vector machine.
Neurocomputing, 2014
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
2013
An adaptive support vector regression based on a new sequence of unified orthogonal polynomials.
Pattern Recognit., 2013
Neural Comput. Appl., 2013
Neurocomputing, 2013
2012
Proceedings of the Advances in Neural Networks - ISNN 2012, 2012
2011
Model selection for least squares support vector regressions based on small-world strategy.
Expert Syst. Appl., 2011
2010
Proceedings of the Advances in Neural Networks, 2010
2009
Weighted solution path algorithm of support vector regression based on heuristic weight-setting optimization.
Neurocomputing, 2009
Proceedings of the Fifth International Conference on Natural Computation, 2009
Proceedings of the Artificial Intelligence and Computational Intelligence, 2009
2008
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008