Sha Fu

674 citations
45 papers · 434 · h-index 12

Impact in

Papers in

Sha Fu

42 papers receiving 404 citations

Peers

Sha Fu
Comparison fields: 5 of 81
  • Management Science and Operations Research 116
  • Artificial Intelligence 145
  • Management Information Systems 34
  • Accounting 43
  • Statistics and Probability 31
Replace Hangjun Zhou with:
Hangjun Zhou China
Zebin Yang United States
Antoni Wibowo Indonesia
Shian-Chang Huang Taiwan
Wang Guoxun China
Javier G. Castellano Spain
Changzheng He China
Brahim Ouhbi Morocco
Arash Ghanbari Iran
Carla Vairetti Chile
Sha Fu relative to Hangjun Zhou China Hangjun Zhou's profile →
Citations per field
00.5×1.5×2.3×
Hangjun Zhou · 1×
Citations per year

Countries citing papers authored by Sha Fu

Since Specialization
Citations

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

Fields of papers citing papers by Sha Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201967
2 202158
3 202233
4 202032
5 202328
6 201624
7 201918
8 200417
9 202216
10 201116
11 202116
12 202212
13 202111
14 20209
15 20188
16 20167
17 20167
18 20156
19 20214
20 20114

About Sha Fu

Sha Fu is a scholar working on Management Science and Operations Research, Information Systems, Artificial Intelligence, Control and Systems Engineering and Ecology, having authored 45 papers that have together received 434 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (22 papers), Advanced Decision-Making Techniques (9 papers), Grey System Theory Applications (6 papers), Imbalanced Data Classification Techniques (4 papers), Evaluation Methods in Various Fields (4 papers), Rough Sets and Fuzzy Logic (4 papers), Research studies in Vietnam (4 papers) and Evaluation and Optimization Models (3 papers). The work is most often cited by research in Management Science and Operations Research (116 citations), Artificial Intelligence (145 citations), Management Information Systems (34 citations), Accounting (43 citations) and Statistics and Probability (31 citations). Sha Fu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Hangjun Zhou, Guang Sun, Jieyu Zhou, Xingxing Zhou, Jing Liu, Yanhua Wang, Ke Wang, Ying Gao, Ding Li and Linli Wang. Their work appears in journals such as Mathematical and Computational Applications, IEEE Access, Scientific Reports, Journal of Applied Sciences and Computers, materials & continua/Computers, materials & continua (Print).

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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