Bin Ning

207 papers receiving 6.7k citations

Bin Ning's Hit Papers

Big Data Analytics in Intelligent Transportation Systems: A Survey 2018 · 820 citations
8200+3+7Years since publication250500750

Peers

Bin Ning
Comparison fields: 5 of 142
  • Transportation 2.4k
  • Industrial and Manufacturing Engineering 3.6k
  • Building and Construction 974
  • Automotive Engineering 821
  • Control and Systems Engineering 1.4k
Replace Gang Xiong with:
Gang Xiong China
Qing He China
Kaizhou Gao China
Bin Ran United States
Dušan Teodorović Serbia
Li Zhu China
Chao Liu China
Meng Wang China
Zhiguang Cao Singapore
Liang Qi China
Bin Ning relative to Gang Xiong China Gang Xiong's profile →
Citations per field
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Citations per year

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-authors

The 25 scholars most cited alongside Bin Ning, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bin Ning Line = papers co-authored together Bin Ning links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 214 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Big Data Analytics in Intelligent Transportation Systems: A Survey
Hit paper breakdown →
2018820
2
A Survey on Energy-Efficient Train Operation for Urban Rail Transit
Hit paper breakdown →
2015309
3 2010297
4 2020226
5 2013197
6 2015182
7 2018179
8 2014166
9 2015152
10 2013152
11 2011133
12 2018109
13 2018108
14 2014103
15 201199
16 201286
17 201685
18 201685
19 201982
20 200673

About Bin Ning

Bin Ning is a scholar working on Industrial and Manufacturing Engineering, Transportation, Control and Systems Engineering, Computer Networks and Communications and Mechanical Engineering, having authored 214 papers that have together received 6.8k indexed citations. Recurring topics across this work include Railway Systems and Energy Efficiency (106 papers), Transportation Planning and Optimization (58 papers), Railway Engineering and Dynamics (50 papers), Adaptive Control of Nonlinear Systems (18 papers), Electrical Contact Performance and Analysis (18 papers), Traffic control and management (15 papers), Traffic Prediction and Management Techniques (15 papers) and Power Line Communications and Noise (14 papers). The work is most often cited by research in Transportation (2.4k citations), Industrial and Manufacturing Engineering (3.6k citations), Building and Construction (974 citations), Automotive Engineering (821 citations) and Control and Systems Engineering (1.4k citations). Bin Ning has collaborated with scholars based in China, Canada and Netherlands. Frequent co-authors include Tao Tang, Hairong Dong, Li Zhu, Fei Richard Yu, Shigen Gao, Yihui Wang, Xin Yang, Yige Wang, Xiang Li and Bart De Schutter. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Intelligent Systems, IEEE Transactions on Vehicular Technology, Transportation Research Part C Emerging Technologies and Neural Computing and Applications.

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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