Ge Cui

481 citations
13 papers · 282 indexed · h-index 10

Impact in

    • Human Mobility and Location-Based Analysis
    • Transportation Planning and Optimization
    • Urban Transport and Accessibility
    • Traffic Prediction and Management Techniques

Papers in

    • Human Mobility and Location-Based Analysis 5
    • Transportation Planning and Optimization 2
    • Data Management and Algorithms 5

Ge Cui

13 papers receiving 272 citations

Peers

Ge Cui
Comparison fields: 5 of 68
  • Transportation 148
  • Building and Construction 87
  • Signal Processing 64
  • Automotive Engineering 57
  • Business and International Management 6
Replace Nevine Labib Georggi with:
Nevine Labib Georggi United States
Can Yang China
Massimiliano Luca Italy
Yao-Jan Wu United States
Fábio Miranda United States
Yongtaek Lim South Korea
Jiwon Kim Australia
Niklas Petersen Germany
Weijia Zhang China
Ge Cui relative to Nevine Labib Georggi United States Nevine Labib Georggi's profile →
Citations per field
00.5×6.3×
Nevine Labib Georggi · 1×
Citations per year

Countries citing papers authored by Ge Cui

Since Specialization
Citations

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

Fields of papers citing papers by Ge Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

13 of 13 papers shown
#Work
1 202116
2 202116
3
BR 2 : A Travel Behavioral Approach to Personalized Route Recommendation Based on GPS Trajectories.
20201
4 202015
5 20202
6 202012
7 201921
8 20199
9 201921
10 201954
11 201799
12 201514
13 20112

About Ge Cui

Ge Cui is a scholar working on Transportation, Signal Processing, Building and Construction, Geography, Planning and Development and Geology, having authored 13 papers that have together received 282 indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (5 papers), Data Management and Algorithms (5 papers), Human Mobility and Location-Based Analysis (5 papers), Automated Road and Building Extraction (2 papers), MRI in cancer diagnosis (2 papers), Geographic Information Systems Studies (2 papers), Transportation Planning and Optimization (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Transportation (148 citations), Building and Construction (87 citations), Signal Processing (64 citations), Automotive Engineering (57 citations) and Business and International Management (6 citations). Ge Cui has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Jun Luo, Xin Wang, Xin Wang, Xin Wang, Xin Wang, Ming Zhong, Hui Mao, Xiaofeng Yang, Ling Ding and Ming Luo. Their work appears in journals such as GeoInformatica, Accident Analysis & Prevention, IEEE Transactions on Intelligent Transportation Systems, International Journal of Digital Earth and Sensors.

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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