Pingxin Wang

1.4k citations
83 papers · 1.0k · h-index 17

Impact in

Papers in

Pingxin Wang

69 papers receiving 971 citations

Peers

Pingxin Wang
Comparison fields: 5 of 106
  • Computational Theory and Mathematics 551
  • Artificial Intelligence 538
  • Information Systems 259
  • Computer Vision and Pattern Recognition 190
  • Management Science and Operations Research 97
Replace Lixiang Shen with:
Lixiang Shen China
Ch. Aswani Kumar India
Yves Lechevallier France
Jin Qian China
Nouman Azam Canada
Andrea Marino Italy
Chien-Chung Chan United States
Antonio J. Rivera Spain
Tapio Elomaa Finland
Yankai Chen China
Pingxin Wang relative to Lixiang Shen China Lixiang Shen's profile →
Citations per field
00.5×10×12.8×
Lixiang Shen · 1×
Citations per year

Countries citing papers authored by Pingxin Wang

Since Specialization
Citations

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

Fields of papers citing papers by Pingxin Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018127
2 2018105
3 201984
4 201957
5 201755
6 198949
7 202139
8 202130
9 202129
10 202027
11 200726
12 202122
13 202221
14 199221
15 202020
16
The Choice of Cost Drivers in Activity-Based Costing: Application at a Chinese Oil Well Cementing Company
201019
17 202218
18 201416
19 202014
20 202314

About Pingxin Wang

Pingxin Wang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Electrical and Electronic Engineering and Control and Systems Engineering, having authored 83 papers that have together received 1.0k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (33 papers), Text and Document Classification Technologies (19 papers), Data Mining Algorithms and Applications (15 papers), Advanced Clustering Algorithms Research (13 papers), Face and Expression Recognition (4 papers), Corporate Finance and Governance (4 papers), Smart Grid and Power Systems (4 papers) and Imbalanced Data Classification Techniques (4 papers). The work is most often cited by research in Computational Theory and Mathematics (551 citations), Artificial Intelligence (538 citations), Information Systems (259 citations), Computer Vision and Pattern Recognition (190 citations) and Management Science and Operations Research (97 citations). Pingxin Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Xibei Yang, Yiyu Yao, Ju‐Sheng Mi, Hualong Yu, Xiangjian Chen, James A. Holcombe, Hua Dai, Yuhua Qian, Keyu Liu and Dun Liu. Their work appears in journals such as International Journal of Machine Learning and Cybernetics, Knowledge-Based Systems, IEEE Access, Spectrochimica Acta Part B Atomic Spectroscopy and International Journal of Approximate Reasoning.

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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