Bin Ning

8.2k total citations · 2 hit papers
217 papers, 6.4k citations indexed

About

Bin Ning is a scholar working on Industrial and Manufacturing Engineering, Transportation and Mechanical Engineering. According to data from OpenAlex, Bin Ning has authored 217 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 102 papers in Industrial and Manufacturing Engineering, 59 papers in Transportation and 56 papers in Mechanical Engineering. Recurrent topics in Bin Ning's work include Railway Systems and Energy Efficiency (102 papers), Transportation Planning and Optimization (58 papers) and Railway Engineering and Dynamics (48 papers). Bin Ning is often cited by papers focused on Railway Systems and Energy Efficiency (102 papers), Transportation Planning and Optimization (58 papers) and Railway Engineering and Dynamics (48 papers). Bin Ning collaborates with scholars based in China, Canada and United States. Bin Ning's co-authors include Tao Tang, Hairong Dong, Li Zhu, F. Richard Yu, Shigen Gao, Yihui Wang, Xin Yang, Bart De Schutter, Xiang Li and Ton van den Boom and has published in prestigious journals such as The Journal of Physical Chemistry B, Journal of Computational Physics and Energy Conversion and Management.

In The Last Decade

Bin Ning

206 papers receiving 6.2k citations

Hit Papers

Big Data Analytics in Intelligent Transportation Systems:... 2015 2026 2018 2022 2018 2015 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bin Ning China 43 3.4k 2.3k 2.1k 1.4k 1.0k 217 6.4k
Gang Xiong China 35 916 0.3× 486 0.2× 784 0.4× 1.0k 0.8× 887 0.9× 447 5.5k
Rob M.P. Goverde Netherlands 40 3.7k 1.1× 2.6k 1.1× 2.2k 1.0× 347 0.3× 175 0.2× 152 4.7k
Andrea D’Ariano Italy 42 4.5k 1.3× 3.4k 1.5× 2.6k 1.2× 472 0.3× 198 0.2× 189 5.7k
Qing He China 39 484 0.1× 1.2k 0.5× 1.7k 0.8× 1.2k 0.9× 618 0.6× 231 5.2k
Shukai Li China 34 1.8k 0.5× 1.4k 0.6× 991 0.5× 708 0.5× 147 0.1× 118 3.1k
Bin Ran United States 47 727 0.2× 3.9k 1.7× 345 0.2× 3.5k 2.6× 555 0.6× 389 7.7k
Kaizhou Gao China 45 4.6k 1.3× 351 0.2× 171 0.1× 1.2k 0.9× 456 0.5× 227 6.8k
Chao Liu China 36 2.8k 0.8× 135 0.1× 1.1k 0.5× 815 0.6× 453 0.5× 200 6.2k
Runwei Cheng Japan 18 2.7k 0.8× 177 0.1× 435 0.2× 1.0k 0.7× 568 0.6× 31 6.1k
Li Zhu China 27 626 0.2× 394 0.2× 244 0.1× 467 0.3× 1.3k 1.3× 184 3.4k

Countries citing papers authored by Bin Ning

Since Specialization
Citations

This map shows the geographic impact of Bin Ning's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bin Ning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Ning more than expected).

Fields of papers citing papers by Bin Ning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bin Ning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bin Ning. The network helps show where Bin Ning may publish in the future.

Co-authorship network of co-authors of Bin Ning

This figure shows the co-authorship network connecting the top 25 collaborators of Bin Ning. A scholar is included among the top collaborators of Bin Ning based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bin Ning. Bin Ning is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Guo, Tao, Bin Ning, Qijun Song, et al.. (2025). A novel sulfur quantum dots-based electrochemical sensor for highly sensitive and specific detection of mancozeb. Microchemical Journal. 209. 112642–112642. 4 indexed citations
2.
Hu, Chunyang, et al.. (2025). A dynamically parameterized 3D hyperchaotic cascade for secure and real-time encryption of medical images. Digital Signal Processing. 170. 105767–105767.
3.
Zeng, Meng, et al.. (2025). DWLBF: a deletable weighted learned Bloom Filter based on data temperature. Journal of King Saud University - Computer and Information Sciences. 37(9).
4.
Ning, Bin, et al.. (2024). A Fitness Distance Correlation-Based Adaptive Differential Evolution for Nonlinear Equations Systems. International Journal of Swarm Intelligence Research. 15(1). 1–22.
5.
Gu, Qiong, Shuijia Li, Wenyin Gong, et al.. (2023). L-SHADE with parameter decomposition for photovoltaic modules parameter identification under different temperature and irradiance. Applied Soft Computing. 143. 110386–110386. 52 indexed citations
6.
Zhu, Li, et al.. (2021). Joint Security and Train Control Design in Blockchain-Empowered CBTC System. IEEE Internet of Things Journal. 9(11). 8119–8129. 62 indexed citations
7.
Liao, Zuowen, Qiong Gu, Shuijia Li, Zhenzhen Hu, & Bin Ning. (2020). An Improved Differential Evolution to Extract Photovoltaic Cell Parameters. IEEE Access. 8. 177838–177850. 19 indexed citations
8.
Zeng, Meng, Bin Ning, Chunyang Hu, et al.. (2020). Hyper-Graph Regularized Kernel Subspace Clustering for Band Selection of Hyperspectral Image. IEEE Access. 8. 135920–135932. 5 indexed citations
9.
Zhu, Li, Yang Li, F. Richard Yu, et al.. (2020). Cross-Layer Defense Methods for Jamming-Resistant CBTC Systems. IEEE Transactions on Intelligent Transportation Systems. 22(11). 7266–7278. 63 indexed citations
10.
Dong, Hairong, Xue Lin, Shigen Gao, Baigen Cai, & Bin Ning. (2019). Neural Networks-Based Sliding Mode Fault-Tolerant Control for High-Speed Trains With Bounded Parameters and Actuator Faults. IEEE Transactions on Vehicular Technology. 69(2). 1353–1362. 41 indexed citations
11.
Wang, Yu, et al.. (2018). Train Rescheduling and Circulation Planning in Case of Complete Blockade for an Urban Rail Transit Line. Transportation Research Board 97th Annual MeetingTransportation Research Board. 3 indexed citations
12.
Schutter, Bart De, et al.. (2014). Origin-Destination Dependent Train Scheduling Problem with Stop-Skipping for Urban Rail Transit Systems. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 11 indexed citations
13.
Wang, Yihui, et al.. (2012). Study on ATO Control Algorithm with Consideration of ATP Speed Limits. Journal of the China Railway Society. 34(5). 59–64. 15 indexed citations
14.
Gao, Shigen, et al.. (2012). Characteristic model-based golden section adaptive control for high-speed train. Chinese Control Conference. 7326–7331. 2 indexed citations
15.
Wang, Yihui, et al.. (2012). Research on the Key Issues of Railway Collision Avoidance System. Journal of the China Railway Society. 34(6). 46–50. 1 indexed citations
16.
Dong, Hairong, Li Li, Bin Ning, & Zhongsheng Hou. (2010). Fuzzy tuning of ATO system in train speed control with multiple working conditions. Chinese Control Conference. 1697–1700. 6 indexed citations
17.
Ning, Bin. (2003). Remote Courseware for Signals and Systems Based on Matlab Web Server. Jisuanji gongcheng. 1 indexed citations
18.
Ning, Bin. (2000). A Study on the Denitration Kinetics of Highly Nitrated Nitrocellulose. Chinese Journal of Explosives and Propellants. 1 indexed citations
19.
Ning, Bin. (1998). Absolute Braking And Relative Distance Braking- Train Operation Control Modes In MovingBlock Systems. WIT transactions on the built environment. 37. 28 indexed citations
20.
Ning, Bin. (1970). Analysis Of Train Braking Accuracy And SafeProtection Distance In Automatic Train Protection(ATP) Systems. WIT transactions on the built environment. 20. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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