Bin Ran

88 papers receiving 2.3k citations

Hit Papers

A hybrid deep learning based traffic flow prediction method and its understanding 2018 · 595 citations
5950+2+5Years since publication100200300400500

Peers

Bin Ran
Comparison fields: 5 of 96
  • Transportation 1.1k
  • Building and Construction 1.5k
  • Control and Systems Engineering 1.3k
  • Automotive Engineering 670
  • Safety, Risk, Reliability and Quality 301
Replace Hwasoo Yeo with:
Hwasoo Yeo South Korea
Lingqiao Qin United States
Ziyuan Pu China
Edward Chung Australia
Ashish Bhaskar Australia
Daiheng Ni United States
Meng Li China
Lelitha Vanajakshi India
Xuegang Ban United States
Nour‐Eddin El Faouzi France
Bin Ran relative to Hwasoo Yeo South Korea Hwasoo Yeo's profile →
Citations per field
00.5×1.7×
Hwasoo Yeo · 1×
Citations per year

Countries citing papers authored by Bin Ran

Since Specialization
Citations

This map shows the geographic impact of Bin Ran'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 Ran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Ran more than expected).

Fields of papers citing papers by Bin Ran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bin Ran. 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 Ran. The network helps show where Bin Ran may publish in the future.

Co-authors

The 25 scholars most cited alongside Bin Ran, 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 Ran Line = papers co-authored together Bin Ran links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 94 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A hybrid deep learning based traffic flow prediction method and its understanding
Hit paper breakdown →
2018595
2 2019178
3 2020147
4 2019115
5 201695
6 202095
7
Short Term Traffic Forecasting Using the Local Linear Regression Model
200275
8 201662
9 202059
10 201955
11 202050
12 201746
13
AN APPLICATION OF NEURAL NETWORK ON TRAFFIC SPEED PREDICTION UNDER ADVERSE WEATHER CONDITION
200343
14 201643
15 202040
16 202037
17 202325
18 201925
19 201720
20 202319

About Bin Ran

Bin Ran is a scholar working on Control and Systems Engineering, Building and Construction, Transportation, Automotive Engineering and Safety, Risk, Reliability and Quality, having authored 94 papers that have together received 2.3k indexed citations. Recurring topics across this work include Traffic control and management (64 papers), Traffic Prediction and Management Techniques (56 papers), Transportation Planning and Optimization (46 papers), Autonomous Vehicle Technology and Safety (22 papers), Traffic and Road Safety (12 papers), Vehicular Ad Hoc Networks (VANETs) (10 papers), Vehicle emissions and performance (7 papers) and Groundwater flow and contamination studies (5 papers). The work is most often cited by research in Transportation (1.1k citations), Building and Construction (1.5k citations), Control and Systems Engineering (1.3k citations), Automotive Engineering (670 citations) and Safety, Risk, Reliability and Quality (301 citations). Bin Ran has collaborated with scholars based in China, United States and Bangladesh. Frequent co-authors include Lingqiao Qin, Xu Qu, Huachun Tan, Yuankai Wu, Zhuxi Jiang, Linchao Li, Linheng Li, Jing Gan, Jian Zhang and Wenqi Lu. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, IEEE Transactions on Intelligent Transportation Systems, IEEE Access, Transportation Research Part C Emerging Technologies and IET Intelligent Transport Systems.

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.

Explore authors with similar magnitude of impact