Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming C Ning, F You Computers & Chemical Engineering 125, 434-448, 2019 | 309 | 2019 |
Data-driven decision making under uncertainty integrating robust optimization with principal component analysis and kernel smoothing methods C Ning, F You Computers & Chemical Engineering 112, 190-210, 2018 | 191 | 2018 |
Data‐driven adaptive nested robust optimization: general modeling framework and efficient computational algorithm for decision making under uncertainty C Ning, F You AIChE Journal 63 (9), 3790-3817, 2017 | 155 | 2017 |
Data-driven adaptive robust unit commitment under wind power uncertainty: A Bayesian nonparametric approach C Ning, F You 🏆 IEEE Transactions on Power Systems 34 (3), 2409-2418, 2019 | 137 | 2019 |
Data-driven stochastic robust optimization: General computational framework and algorithm leveraging machine learning for optimization under uncertainty in the big data era C Ning, F You Computers & Chemical Engineering 111, 115-133, 2018 | 121 | 2018 |
A data‐driven multistage adaptive robust optimization framework for planning and scheduling under uncertainty C Ning, F You AIChE Journal 63 (10), 4343-4369, 2017 | 117 | 2017 |
Data-driven Wasserstein distributionally robust optimization for biomass with agricultural waste-to-energy network design under uncertainty C Ning, F You Applied Energy 255, 113857, 2019 | 73 | 2019 |
Operational optimization of industrial steam systems under uncertainty using data‐D riven adaptive robust optimization L Zhao, C Ning, F You AIChE Journal 65 (7), e16500, 2019 | 53 | 2019 |
Adaptive robust optimization with minimax regret criterion: Multiobjective optimization framework and computational algorithm for planning and scheduling under uncertainty C Ning, F You Computers & Chemical Engineering 108, 425-447, 2018 | 50 | 2018 |
Hidden Markov model-based statistics pattern analysis for multimode process monitoring: an index-switching scheme C Ning, M Chen, D Zhou Industrial & Engineering Chemistry Research 53 (27), 11084-11095, 2014 | 48 | 2014 |
Data‐driven distributionally robust optimization of shale gas supply chains under uncertainty J Gao, C Ning, F You AIChE Journal 65 (3), 947-963, 2019 | 40 | 2019 |
Deep learning based distributionally robust joint chance constrained economic dispatch under wind power uncertainty C Ning, F You IEEE Transactions on Power Systems 37 (1), 191-203, 2021 | 39 | 2021 |
Incorporating agricultural waste-to-energy pathways into biomass product and process network through data-driven nonlinear adaptive robust optimization J Nicoletti, C Ning, F You Energy 180, 556-571, 2019 | 36 | 2019 |
Online learning based risk-averse stochastic MPC of constrained linear uncertain systems C Ning, F You Automatica 125, 109402, 2021 | 32 | 2021 |
Sparse contribution plot for fault diagnosis of multimodal chemical processes C Ning, M Chen, D Zhou IFAC-PapersOnLine 48 (21), 619-626, 2015 | 23 | 2015 |
Day-ahead chance-constrained energy management of energy hubs: a distributionally robust approach J Cao, B Yang, S Zhu, C Ning, X Guan CSEE Journal of Power and Energy Systems 8 (3), 812-825, 2021 | 20 | 2021 |
A transformation-proximal bundle algorithm for multistage adaptive robust optimization and application to constrained robust optimal control C Ning, F You Automatica 113, 108802, 2020 | 14 | 2020 |
Multistage scheduling of regional power grids against sequential outage and power uncertainties H Qiu, L Wang, W Gu, G Pan, C Ning, Z Wu, Q Sun IEEE Transactions on Smart Grid 13 (6), 4624-4637, 2022 | 9 | 2022 |
A data-driven robust optimization approach to operational optimization of industrial steam systems under uncertainty L Zhao, C Ning, F You Computer aided chemical engineering 46, 1399-1404, 2019 | 9 | 2019 |
Data-driven robust MILP model for scheduling of multipurpose batch processes under uncertainty C Ning, F You 2016 IEEE 55th Conference on Decision and Control (CDC), 6180-6185, 2016 | 7 | 2016 |