4.2021 - Boeing - Data-driven Performance Evaluation within ZGGG TMA
5.2019 - Boeing - Data-driven TP Research for ETA within the TMA
6.2017 - Boeing&COMAC Decision Support Tool for TMA Operation (III)
7.2015 - Boeing&COMAC Decision Support Tool for TMA Operation (II)
8.2013 - Boeing&COMAC Decision Support Tool for TMA Operation (I)
9.2019 - 民航局空管局 - 大型機場全向進場飛行程序設計與運行專項研究
10.2017 - 民航局空管局 - CCO/CDO 連續爬升與下降運行 III 期項目
11.2016 - 民航局空管局 - CCO/CDO 連續爬升與下降運行 II 期項目
12.2015 - 民航局空管局 - CCO/CDO 連續爬升與下降運行 I 期項目
13.2021 - 中南空管局 - 基于數據的廣州進場運行效率研究
14.2020 - 中南空管局 - 廣州進場管理系統應用效率分析研究
15.2017 - 中南空管局 - 長沙進場管理系統應用效率分析研究
論文專著教材及
專利軟著
1.Peng Z H, Zhang J F*, Xiang T, et al. Benefits Derived from Arrival Management and Wake Turbulence Re-Categorization in China [J]. Transportation Research Record, 2021, 5, p. 03611981211017898. [SCI]
2.Gui X H, Zhang J F*, PENG Z H. Trajectory clustering for arrival aircraft via new trajectory representation [J]. Journal of Systems Engineering and Electronics. 2021, 32(2): 473 – 486. [SCI]
3.Zhang J F*, Zhao P, Zhang Y, et al. Criteria selection and multi-objective optimization of aircraft landing problem [J]. Journal of Air Transport Management, 2020, 82:101734 [SSCI]
4.Zhang J F*, Liu J, Hu R, et al. Online four dimensional trajectory prediction method based on aircraft intent updating[J].Aerospace Science and Technology, 2018, 77: 774-787 [SCI]
5.Li Z Y, Zhang J F*, Hu S S. Incremental Support Vector Machine Algorithm based on Multi-Kernel Learning.[J].Journal of Systems Engineering and Electronics, 2011, 22(4):702-706 [SCI]
6.Zhang J F*, Zhao P L, Yang C W, et al. A new meta⁃heuristic approach for aircraft landing problem[J].Transactions of NUAA, 2020, 37(2): 197-208 [EI]
7.M T Shi, Zhang J F*, T T Ge, Z X Zheng. A Combined Arrival and Departure Scheduling for Multi-airport System[J]. Transactions of NUAA, 2017, 34(5): 578-585 [EI]
