| Adaptive soft sensor modeling framework based on just-in-time learning and kernel partial least squares regression for nonlinear multiphase batch processes H Jin, X Chen, J Yang, L Wu Computers & Chemical Engineering 71, 77-93, 2014 | 112 | 2014 |
| Multi-model adaptive soft sensor modeling method using local learning and online support vector regression for nonlinear time-variant batch processes H Jin, X Chen, J Yang, H Zhang, L Wang, L Wu Chemical Engineering Science 131, 282-303, 2015 | 92 | 2015 |
| Adaptive soft sensor development based on online ensemble Gaussian process regression for nonlinear time-varying batch processes H Jin, X Chen, L Wang, K Yang, L Wu Industrial & Engineering Chemistry Research 54 (30), 7320-7345, 2015 | 76 | 2015 |
| A matrix-cube-based estimation of distribution algorithm for the distributed assembly permutation flow-shop scheduling problem ZQ Zhang, B Qian, R Hu, HP Jin, L Wang Swarm and Evolutionary Computation 60, 100785, 2021 | 63 | 2021 |
| Soft sensor development for online quality prediction of industrial batch rubber mixing process using ensemble just-in-time Gaussian process regression models K Yang, H Jin, X Chen, J Dai, L Wang, D Zhang Chemometrics and Intelligent Laboratory Systems 155, 170-182, 2016 | 63 | 2016 |
| Probabilistic wind power forecasting using selective ensemble of finite mixture Gaussian process regression models H Jin, L Shi, X Chen, B Qian, B Yang, H Jin Renewable Energy 174, 1-18, 2021 | 57 | 2021 |
| Just-in-time learning based soft sensor with variable selection and weighting optimized by evolutionary optimization for quality prediction of nonlinear processes B Pan, H Jin, L Wang, B Qian, X Chen, S Huang, J Li Chemical Engineering Research and Design 144, 285-299, 2019 | 43 | 2019 |
| Dual learning-based online ensemble regression approach for adaptive soft sensor modeling of nonlinear time-varying processes H Jin, X Chen, L Wang, K Yang, L Wu Chemometrics and Intelligent Laboratory Systems 151, 228-244, 2016 | 43 | 2016 |
| Online local learning based adaptive soft sensor and its application to an industrial fed-batch chlortetracycline fermentation process H Jin, X Chen, J Yang, L Wang, L Wu Chemometrics and Intelligent Laboratory Systems 143, 58-78, 2015 | 43 | 2015 |
| Soft sensor development based on the hierarchical ensemble of Gaussian process regression models for nonlinear and non-Gaussian chemical processes L Wang, H Jin, X Chen, J Dai, K Yang, D Zhang Industrial & Engineering Chemistry Research 55 (28), 7704-7719, 2016 | 40 | 2016 |
| A matrix cube-based estimation of distribution algorithm for the energy-efficient distributed assembly permutation flow-shop scheduling problem ZQ Zhang, R Hu, B Qian, HP Jin, L Wang, JB Yang Expert Systems with Applications 194, 116484, 2022 | 36 | 2022 |
| Ensemble just-in-time learning framework through evolutionary multi-objective optimization for soft sensor development of nonlinear industrial processes H Jin, B Pan, X Chen, B Qian Chemometrics and Intelligent Laboratory Systems 184, 153-166, 2019 | 35 | 2019 |
| Hybrid intelligent control of substrate feeding for industrial fed-batch chlortetracycline fermentation process H Jin, X Chen, J Yang, L Wu, L Wang ISA transactions 53 (6), 1822-1837, 2014 | 34 | 2014 |
| Evolutionary optimization based pseudo labeling for semi-supervised soft sensor development of industrial processes H Jin, Z Li, X Chen, B Qian, B Yang, J Yang Chemical Engineering Science 237, 116560, 2021 | 33 | 2021 |
| A generative image fusion approach based on supervised deep convolution network driven by weighted gradient flow M Wang, X Liu, H Jin Image and Vision Computing 86, 1-16, 2019 | 26 | 2019 |
| Semi-supervised ensemble support vector regression based soft sensor for key quality variable estimation of nonlinear industrial processes with limited labeled data Z Li, H Jin, S Dong, B Qian, B Yang, X Chen Chemical Engineering Research and Design 179, 510-526, 2022 | 23 | 2022 |
| Ensemble Just‐In‐Time Learning‐Based Soft Sensor for Mooney Viscosity Prediction in an Industrial Rubber Mixing Process H Jin, J Li, M Wang, B Qian, B Yang, Z Li, L Shi Advances in Polymer Technology 2020 (1), 6575326, 2020 | 21 | 2020 |
| A matrix-cube-based estimation of distribution algorithm for no-wait flow-shop scheduling with sequence-dependent setup times and release times B Qian, ZQ Zhang, R Hu, HP Jin, JB Yang IEEE Transactions on Systems, Man, and Cybernetics: Systems 53 (3), 1492-1503, 2022 | 18 | 2022 |
| Soft sensor development for nonlinear industrial processes based on ensemble just-in-time extreme learning machine through triple-modal perturbation and evolutionary … B Pan, H Jin, B Yang, B Qian, Z Zhao Industrial & Engineering Chemistry Research 58 (38), 17991-18006, 2019 | 17 | 2019 |
| A Q-learning-based hyper-heuristic evolutionary algorithm for the distributed flexible job-shop scheduling problem with crane transportation ZQ Zhang, FC Wu, B Qian, R Hu, L Wang, HP Jin Expert Systems with Applications 234, 121050, 2023 | 15 | 2023 |
