Chun-Min Yu

423 citations
44 papers · 343 · h-index 11

Impact in

Papers in

Chun-Min Yu

37 papers receiving 338 citations

Peers

Chun-Min Yu
Comparison fields: 5 of 50
  • Statistics, Probability and Uncertainty 169
  • Industrial and Manufacturing Engineering 143
  • Medical Laboratory Technology 11
  • Statistics and Probability 53
  • Management Science and Operations Research 64
Replace Nani Kurniati with:
Nani Kurniati Indonesia
Gu-Hong Lin Taiwan
Timothy S. Vaughan United States
Tsang-Chuan Chang Taiwan
Chunghun Ha South Korea
Guoqing Cheng China
Parveen S. Goel United States
Adel A. Ghobbar Netherlands
Kit‐Nam Francis Leung Hong Kong
Changchao Gu China
Chun-Min Yu relative to Nani Kurniati Indonesia Nani Kurniati's profile →
Citations per field
00.5×1.5×1.8×
Nani Kurniati · 1×
Citations per year

Countries citing papers authored by Chun-Min Yu

Since Specialization
Citations

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

Fields of papers citing papers by Chun-Min Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun-Min Yu. 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 Chun-Min Yu. The network helps show where Chun-Min Yu may publish in the future.

Co-authors

The 13 scholars most cited alongside Chun-Min Yu, 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 Chun-Min Yu Line = papers co-authored together Chun-Min Yu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201961
2 201937
3 202033
4 201625
5 202020
6 202018
7 202012
8 202211
9 201911
10 202111
11 202111
12 202110
13 202010
14 20219
15 20208
16 20217
17 20225
18 20185
19 20215
20 20224

About Chun-Min Yu

Chun-Min Yu is a scholar working on Statistics, Probability and Uncertainty, Industrial and Manufacturing Engineering, Management Information Systems, Strategy and Management and Management Science and Operations Research, having authored 44 papers that have together received 343 indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (26 papers), Manufacturing Process and Optimization (15 papers), Industrial Vision Systems and Defect Detection (10 papers), Multi-Criteria Decision Making (8 papers), Quality and Supply Management (7 papers), Quality and Management Systems (7 papers), Fault Detection and Control Systems (4 papers) and Advanced Statistical Methods and Models (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (169 citations), Industrial and Manufacturing Engineering (143 citations), Medical Laboratory Technology (11 citations), Statistics and Probability (53 citations) and Management Science and Operations Research (64 citations). Chun-Min Yu has collaborated with scholars based in Taiwan, Yemen and China. Frequent co-authors include Kuen‐Suan Chen, Kuo-Ping Lin, Tsang-Chuan Chang, Kuei‐Kuei Lai, Win‐Jet Luo, Mei‐Ling Huang, Tsung‐Yu Huang, Hsuan‐Yu Chen, Mingyuan Li and Chun–Ming Yang. Their work appears in journals such as Applied Sciences, Annals of Operations Research, International Journal of Reliability Quality and Safety Engineering, Journal of Intelligent & Fuzzy Systems and Scientific Reports.

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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