| A novel hybrid method integrating ICA-PCA with relevant vector machine for multivariate process monitoring Y Xu, SQ Shen, YL He, QX Zhu IEEE Transactions on Control Systems Technology 27 (4), 1780-1787, 2018 | 92 | 2018 |
| Novel manifold learning based virtual sample generation for optimizing soft sensor with small data XH Zhang, Y Xu, YL He, QX Zhu ISA transactions 109, 229-241, 2021 | 74 | 2021 |
| A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry YL He, PJ Wang, MQ Zhang, QX Zhu, Y Xu Energy 147, 418-427, 2018 | 71 | 2018 |
| Novel soft sensor development using echo state network integrated with singular value decomposition: Application to complex chemical processes YL He, Y Tian, Y Xu, QX Zhu Chemometrics and Intelligent Laboratory Systems 200, 103981, 2020 | 69 | 2020 |
| Fault diagnosis using novel AdaBoost based discriminant locality preserving projection with resamples YL He, Y Zhao, X Hu, XN Yan, QX Zhu, Y Xu Engineering Applications of Artificial Intelligence 91, 103631, 2020 | 65 | 2020 |
| Novel virtual sample generation using conditional GAN for developing soft sensor with small data QX Zhu, KR Hou, ZS Chen, ZS Gao, Y Xu, YL He Engineering Applications of Artificial Intelligence 106, 104497, 2021 | 57 | 2021 |
| Novel double-layer bidirectional LSTM network with improved attention mechanism for predicting energy consumption YL He, L Chen, Y Gao, JH Ma, Y Xu, QX Zhu ISA transactions 127, 350-360, 2022 | 56 | 2022 |
| System dynamic modeling of energy savings in the US food industry Y Xu, J Szmerekovsky Journal of Cleaner Production 165, 13-26, 2017 | 55 | 2017 |
| Combining FAP, MAP and correlation analysis for multivariate alarm thresholds optimization in industrial process L Han, H Gao, Y Xu, Q Zhu Journal of Loss Prevention in the Process Industries 40, 471-478, 2016 | 49 | 2016 |
| An imbalanced multifault diagnosis method based on bias weights AdaBoost X Jiang, Y Xu, W Ke, Y Zhang, QX Zhu, YL He IEEE Transactions on Instrumentation and Measurement 71, 1-8, 2022 | 48 | 2022 |
| Dealing with small sample size problems in process industry using virtual sample generation: a Kriging-based approach QX Zhu, ZS Chen, XH Zhang, A Rajabifard, Y Xu, YQ Chen Soft Computing 24, 6889-6902, 2020 | 47 | 2020 |
| Evaluating the environmental efficiency of the US airline industry using a directional distance function DEA approach Y Xu, YS Park, JD Park, W Cho Journal of Management Analytics 8 (1), 1-18, 2021 | 46 | 2021 |
| Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model Y Han, Q Zhu, Z Geng, Y Xu Applied Thermal Engineering 115, 280-291, 2017 | 46 | 2017 |
| A hierarchical structure of extreme learning machine (HELM) for high-dimensional datasets with noise YL He, ZQ Geng, Y Xu, QX Zhu Neurocomputing 128, 407-414, 2014 | 45 | 2014 |
| A virtual sample generation approach based on a modified conditional GAN and centroidal Voronoi tessellation sampling to cope with small sample size problems: Application to … ZS Chen, KR Hou, MY Zhu, Y Xu, QX Zhu Applied Soft Computing 101, 107070, 2021 | 39 | 2021 |
| Improved locality preserving projections based on heat-kernel and cosine weights for fault classification in complex industrial processes N Zhang, Y Xu, QX Zhu, YL He IEEE Transactions on Reliability 72 (1), 204-213, 2022 | 38 | 2022 |
| Systematic rationalization approach for multivariate correlated alarms based on interpretive structural modeling and Likert scale H Gao, Y Xu, X Gu, X Lin, Q Zhu Chinese Journal of Chemical Engineering 23 (12), 1987-1996, 2015 | 37 | 2015 |
| Novel stacked input-enhanced supervised autoencoder integrated with gated recurrent unit for soft sensing Y Tian, Y Xu, QX Zhu, YL He IEEE Transactions on Instrumentation and Measurement 71, 1-9, 2022 | 36 | 2022 |
| A novel scoring function based on family transfer entropy for Bayesian networks learning and its application to industrial alarm systems QQ Meng, QX Zhu, HH Gao, YL He, Y Xu Journal of Process Control 76, 122-132, 2019 | 36 | 2019 |
| A novel prediction intervals method integrating an error & self-feedback extreme learning machine with particle swarm optimization for energy consumption robust prediction Y Xu, M Zhang, L Ye, Q Zhu, Z Geng, YL He, Y Han Energy 164, 137-146, 2018 | 35 | 2018 |
