Ding-An Chiang

677 citations
31 papers · 534 · h-index 12

Impact in

Papers in

Ding-An Chiang

27 papers receiving 486 citations

Peers

Ding-An Chiang
Comparison fields: 5 of 72
  • Management Science and Operations Research 212
  • Statistics and Probability 116
  • Signal Processing 107
  • Computational Theory and Mathematics 144
  • Artificial Intelligence 256
Replace J.M. Zurita with:
J.M. Zurita Spain
Ramakanta Mohanty India
Martin Spott United Kingdom
Nguyen Tho Thong Vietnam
Yungho Leu Taiwan
Vahid Khatibi Iran
Tomáš Tichý Czechia
Marcel Holsheimer Netherlands
Heng‐Ru Zhang China
Daniel P. Connors United States
Ding-An Chiang relative to J.M. Zurita Spain J.M. Zurita's profile →
Citations per field
00.5×3.8×
J.M. Zurita · 1×
Citations per year

Countries citing papers authored by Ding-An Chiang

Since Specialization
Citations

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

Fields of papers citing papers by Ding-An Chiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ding-An Chiang. 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 Ding-An Chiang. The network helps show where Ding-An Chiang may publish in the future.

Co-authors

The 17 scholars most cited alongside Ding-An Chiang, 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 Ding-An Chiang Line = papers co-authored together Ding-An Chiang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999200
2 200050
3 201034
4 200829
5 200024
6 200723
7 201020
8 199719
9 198817
10 200116
11 198916
12 200915
13 199810
14 20089
15 19968
16 19888
17 20057
18 20106
19 20015
20 20103

About Ding-An Chiang

Ding-An Chiang is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Signal Processing and Computational Theory and Mathematics, having authored 31 papers that have together received 534 indexed citations. Recurring topics across this work include Data Management and Algorithms (10 papers), Advanced Database Systems and Queries (9 papers), Rough Sets and Fuzzy Logic (9 papers), Data Mining Algorithms and Applications (8 papers), Customer churn and segmentation (6 papers), Logic, Reasoning, and Knowledge (5 papers), Advanced Text Analysis Techniques (4 papers) and Imbalanced Data Classification Techniques (3 papers). The work is most often cited by research in Management Science and Operations Research (212 citations), Statistics and Probability (116 citations), Signal Processing (107 citations), Computational Theory and Mathematics (144 citations) and Artificial Intelligence (256 citations). Ding-An Chiang has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Nancy Lin, Yifan Wang, Li Yan Yuan, Huan‐Chao Keh, Shaoping Chen, Huihua Huang, Mei‐Hua Hsu, Yi-Hsin Wang, Chun-Chi Chen and Wei Chen. Their work appears in journals such as Expert Systems with Applications, Fuzzy Sets and Systems, Knowledge-Based Systems, International Journal of Intelligent Systems and IEEE Transactions on Knowledge and Data Engineering.

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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