代表性论文专著
1. Liang, X., Liu, Z., Wang, J., Jin, X., Du, Z., Uncertainty quantification-based robust deep learning for building energy systems considering distribution shift problem, Applied Energy, 2023, 337, 120889
2. Li P., Anduv B., Zhu X., Jin X., Du Z.,Diagnosis for the refrigerant undercharge fault of chiller using deep belief network enhanced extreme learning machine, (2023) Sustainable Energy Technologies and Assessments, 55, 102977
3. Zhimin Du, Xinbin Liang, Siliang Chen, Xu Zhu, Kang Chen, Xinqiao Jin, Knowledge-infused deep learning diagnosis model with self-assessment for smart management in HVAC systems, Energy, Volume 263, Part D, 2023, 125969, ISSN 0360-5442
4. Xinbin Liang, Xu Zhu, Kang Chen, Siliang Chen, Xinqiao Jin, Zhimin Du*, Endowing data-driven models with rejection ability: Out-of-distribution detection and confidence estimation for black-box models of building energy systems, Energy,2022,125858
5. Chen, S., Chen, K., Zhu, X., Jin, X., Du, Z.*, Deep learning-based image recognition method for on-demand defrosting control to save energy in commercial energy systems(2022) Applied Energy, 324, 119702
6. Chen, S., Zhu, X., Chen, K., Liu, Z., Li, P., Liang, X., Jin, X., Du, Z.*, Applying deep learning-based regional feature recognition from macro-scale image to assist energy saving and emission reduction in industrial energy systems, Journal of Advanced Research,2023, 46, 189-197
7. Li, P., Anduv, B., Zhu, X., Jin, X., Du, Z.*, Across working conditions fault diagnosis for chillers based on IoT intelligent agent with deep learning model,(2022) Energy and Buildings, 268, 112188
8. Pengcheng Li, Zhurong Liu, Burkay Anduv, Xu Zhu, Xinqiao Jin, Zhimin Du*, Diagnosis for multiple faults of chiller using ELM-KNN model enhanced by multi-label learning and specific feature combinations[J], Building and Environment, Volume 214,2022,108904
9. Liang, X., Li, P., Chen, S., Jin, X., Du, Z.*, Partial domain adaption based prediction calibration methodology for fault detection and diagnosis of chillers under variable operational condition scenarios (2022) Building and Environment, 217, 109099
10. Chen, K., Zhu, X., Anduv, B., Jin, X., Du, Z.*, Digital twins model and its updating method for heating, ventilation and air conditioning system using broad learning system algorithm,(2022) Energy, 251, 124040
11. Xu Zhu, Kang Chen, Burkay Anduv, Xinqiao Jin, Zhimin Du. Transfer learning based methodology for migration and application of fault detection and diagnosis between building chillers for improving energy efficiency [J]. Building and Environment, 2021, 200: 107957.
12. Zhang S, Zhu X, Anduv B, et al. Fault detection and diagnosis for the screw chillers using multi-region XGBoost model[J]. Science and Technology for the Built Environment, 2021, 27(5): 608-623.
13. Zhu X, Zhang S, Jin X, et al. Deep learning based reference model for operational risk evaluation of screw chillers for energy efficiency[J]. Energy, 2020, 213: 118833.
14. Zhu X, Shi T, Jin X, et al. Multi-sensor information fusion based control for VAV systems using thermal comfort constraints[J]. Building Simulation, 2020: 1-16.
15. Chen Z, Zhu X, Jin X, et al. Machine learning enhanced inverse modeling method for variable speed air conditioning systems[J]. International Journal of Refrigeration, 2020, 118: 311-324.
16. Du Z, Jin X, Zhu Y, et al. Development and application of hardware-in-the-loop simulation for the HVAC systems[J]. Science and Technology for the Built Environment, 2019, 25(10): 1482-1493.
17. Zhu X, Du Z, Jin X, et al. Fault diagnosis based operation risk evaluation for air conditioning systems in data centers[J]. Building and Environment, 2019, 163: 106319.
18. Zhu X, Du Z, Chen Z, et al. Hybrid model based refrigerant charge fault estimation for the data centre air conditioning system[J]. International Journal of Refrigeration, 2019, 106: 392-406.
19. Du Z, Chen L, Jin X. Data-driven based reliability evaluation for measurements of sensors in a vapor compression system[J]. Energy, 2017, 122: 237-248.
20. Zhimin Du, Xinqiao Jin, Xing Fang, Bo Fan. A dual-benchmark based energy analysis method to evaluate control strategies for building HVAC systems [J]. Applied Energy, 2016, 183:700-714.
21. Zhimin Du, Piotr A. Domanski, W.Vance Payne. Effect of common faults on the performance of different types of vapor compression systems [J]. Applied Thermal Engineering, 2016, 98: 61-72.
22. Zhimin Du, Xinqiao Jin, Bo Fan. Evaluation of operation and control in HVAC (heating, ventilation and air conditioning) system using exergy analysis method [J]. Energy, 2015, 89: 372-381.
23. Zhimin Du, Peifan Xu, Xinqiao Jin, Qiaoling Liu. Temperature sensor placement optimization for VAV control using CFD–BES co-simulation strategy [J]. Building and Environment, 2015, 85: 104-113.