Peng Xie

2.4k citations
43 papers · 1.7k · 1 hit paper · h-index 18

Impact in

Papers in

Peng Xie

37 papers receiving 1.7k citations

Peng Xie's Hit Papers

Urban flow prediction from spatiotemporal data using machine learning: A survey 2020 · 215 citations
2150+2+4Years since publication50100150200

Peers

Peng Xie
Comparison fields: 5 of 166
  • Transportation 261
  • Building and Construction 311
  • Complementary and alternative medicine 186
  • General Engineering 25
  • Critical Care and Intensive Care Medicine 60
Replace Zhiqiang Lv with:
Zhiqiang Lv China
Kerstin Thurow Germany
Wenhua Li China
Xiao Wu China
Amita Jain India
Fan Zhang China
Wen Chen China
Kezhi Li United Kingdom
Guijuan Zhang China
Peng Xie relative to Zhiqiang Lv China Zhiqiang Lv's profile →
Citations per field
00.5×10×15×20×25×
Zhiqiang Lv · 1×
Citations per year

Countries citing papers authored by Peng Xie

Since Specialization
Citations

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

Fields of papers citing papers by Peng Xie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004363
2
Urban flow prediction from spatiotemporal data using machine learning: A survey
Hit paper breakdown →
2020215
3 2019193
4 2004138
5 2021100
6 201993
7 201685
8 202074
9 202066
10 202151
11 202044
12 201937
13 202136
14 202333
15 202326
16 202020
17 202018
18 202318
19 202016
20 201511

About Peng Xie

Peng Xie is a scholar working on Electrical and Electronic Engineering, Building and Construction, Transportation, Biomedical Engineering and Automotive Engineering, having authored 43 papers that have together received 1.7k indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (8 papers), Human Mobility and Location-Based Analysis (7 papers), Data Management and Algorithms (3 papers), Intensive Care Unit Cognitive Disorders (3 papers), Bone Tissue Engineering Materials (3 papers), Transportation Planning and Optimization (3 papers), Dental Implant Techniques and Outcomes (3 papers) and Long-Term Effects of COVID-19 (2 papers). The work is most often cited by research in Transportation (261 citations), Building and Construction (311 citations), Complementary and alternative medicine (186 citations), General Engineering (25 citations) and Critical Care and Intensive Care Medicine (60 citations). Peng Xie has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Kelvin Chan, Yi‐Zeng Liang, Tianrui Li, Shengdong Du, Xin Yang, Jia Liu, Junbo Zhang, Fei Teng, Jia Liu and Chen Wang. Their work appears in journals such as Information Fusion, Information Sciences, IEEE Transactions on Knowledge and Data Engineering, Scientific Reports and Ceramics International.

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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