| A mixture of variational canonical correlation analysis for nonlinear and quality-relevant process monitoring Y Liu, B Liu, X Zhao, M Xie IEEE Transactions on Industrial Electronics 65 (8), 6478-6486, 2017 | 121 | 2017 |
| Hybrid feedback feedforward: An efficient design of adaptive neural network control Y Pan, Y Liu, B Xu, H Yu Neural Networks 76, 122-134, 2016 | 113 | 2016 |
| Composite learning from adaptive backstepping neural network control Y Pan, T Sun, Y Liu, H Yu Neural Networks 95, 134-142, 2017 | 101 | 2017 |
| Rebooting data-driven soft-sensors in process industries: A review of kernel methods Y Liu, M Xie Journal of Process Control 89, 58-73, 2020 | 90 | 2020 |
| Fault diagnosis and prognosis of wastewater processes with incomplete data by the auto-associative neural networks and ARMA model H Xiao, D Huang, Y Pan, Y Liu, K Song Chemometrics and Intelligent Laboratory Systems 161, 96-107, 2017 | 89 | 2017 |
| Resilience design method based on meta-structure: A case study of offshore wind farm Q Feng, X Zhao, D Fan, B Cai, Y Liu, Y Ren Reliability Engineering & System Safety 186, 232-244, 2019 | 82 | 2019 |
| Statistical monitoring of wastewater treatment plants using variational Bayesian PCA Y Liu, Y Pan, Z Sun, D Huang Industrial & Engineering Chemistry Research 53 (8), 3272-3282, 2014 | 79 | 2014 |
| Improving dewaterability of anaerobically digested sludge by combination of persulfate and zero valent iron K Song, X Zhou, Y Liu, GJ Xie, D Wang, T Zhang, C Liu, P Liu, B Zhou, ... Chemical Engineering Journal 295, 436-442, 2016 | 78 | 2016 |
| Optimal sensor placement methodology of hydraulic control system for fault diagnosis X Kong, B Cai, Y Liu, H Zhu, Y Liu, H Shao, C Yang, H Li, T Mo Mechanical Systems and Signal Processing 174, 109069, 2022 | 71 | 2022 |
| Reliability modeling and analysis of load-sharing systems with continuously degrading components X Zhao, B Liu, Y Liu IEEE Transactions on Reliability 67 (3), 1096-1110, 2018 | 69 | 2018 |
| A supervised bidirectional long short-term memory network for data-driven dynamic soft sensor modeling CF Lui, Y Liu, M Xie IEEE Transactions on Instrumentation and Measurement 71, 1-13, 2022 | 67 | 2022 |
| Evaluation of data-driven models for predicting the service life of concrete sewer pipes subjected to corrosion X Li, F Khademi, Y Liu, M Akbari, C Wang, PL Bond, J Keller, G Jiang Journal of environmental management 234, 431-439, 2019 | 67 | 2019 |
| Development of interval soft sensors using enhanced just-in-time learning and inductive confidence predictor Y Liu, D Huang, Y Li Industrial & engineering chemistry research 51 (8), 3356-3367, 2012 | 61 | 2012 |
| Life cycle cost analysis considering multiple dependent degradation processes and environmental influence B Liu, X Zhao, G Liu, Y Liu Reliability Engineering & System Safety 197, 106784, 2020 | 47 | 2020 |
| Date-driven soft-sensor design for biological wastewater treatment using deep neural networks and genetic algorithms Y Qiu, Y Liu, D Huang Journal of chemical engineering of Japan 49 (10), 925-936, 2016 | 47 | 2016 |
| Development of a novel adaptive soft-sensor using variational Bayesian PLS with accounting for online identification of key variables Y Liu, Y Pan, D Huang Industrial & Engineering Chemistry Research 54 (1), 338-350, 2015 | 46 | 2015 |
| Development of RVM-based multiple-output soft sensors with serial and parallel stacking strategies Y Liu, B Liu, X Zhao, M Xie IEEE Transactions on Control Systems Technology 27 (6), 2727-2734, 2018 | 44 | 2018 |
| Polyhydroxyalkanoates in waste activated sludge enhances anaerobic methane production through improving biochemical methane potential instead of hydrolysis rate Q Wang, J Sun, C Zhang, GJ Xie, X Zhou, J Qian, G Yang, G Zeng, Y Liu, ... Scientific Reports 6 (1), 19713, 2016 | 44 | 2016 |
| Improved sulfide mitigation in sewers through on-line control of ferrous salt dosing R Ganigué, G Jiang, Y Liu, K Sharma, YC Wang, J Gonzalez, T Nguyen, ... Water research 135, 302-310, 2018 | 40 | 2018 |
| Prediction of concrete corrosion in sewers with hybrid Gaussian processes regression model Y Liu, Y Song, J Keller, P Bond, G Jiang RSC advances 7 (49), 30894-30903, 2017 | 40 | 2017 |
