Ming-Shong Lan

798 citations
14 papers · 554 indexed · h-index 7
Topics
Fuzzy Logic and Control Systems (8 papers)Neural Networks and Applications (7 papers)Advanced machining processes and optimization (3 papers)
Partner nations
United StatesJapan

In The Last Decade

Ming-Shong Lan

13 papers receiving 508 citations

Peers

Ming-Shong Lan
Comparison fields: 5 of 69
  • Artificial Intelligence 402
  • Control and Systems Engineering 98
  • Mechanical Engineering 78
  • Computational Theory and Mathematics 74
  • Statistics and Probability 67
Replace Chia-Hung Hsu with:
Chia-Hung Hsu Taiwan
N. Yubazaki Japan
Philip Thrift United States
Maowen Nie Singapore
Nohé R. Cázarez-Castro Mexico
Xueming Ding China
M. Khalid Malaysia
Gang Leng United Kingdom
Nor Hidayati Abdul Aziz Malaysia
Fernando Gaxiola Mexico
Ming-Shong Lan relative to Chia-Hung Hsu Taiwan Chia-Hung Hsu's profile →
Citations per field
00.5×2.5×
Chia-Hung Hsu · 1×
Citations per year

Countries citing papers authored by Ming-Shong Lan

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Shong Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming-Shong Lan. 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 Ming-Shong Lan. The network helps show where Ming-Shong Lan may publish in the future.

Co-authorship network of co-authors of Ming-Shong Lan

This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Shong Lan. A scholar is included among the top collaborators of Ming-Shong Lan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming-Shong Lan. Ming-Shong Lan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 0
2 2
3 1
4
Efficient methods for fuzzy rule extraction from numerical data
4
5 20
6 114
7 82
8 226
9 6
10 6
11 18
12 50
13 5
14 20

About Ming-Shong Lan

Ming-Shong Lan is a scholar working on Artificial Intelligence, Environmental Engineering and Control and Systems Engineering, having authored 14 papers that have together received 554 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (8 papers), Neural Networks and Applications (7 papers) and Advanced machining processes and optimization (3 papers). The work is most often cited by research in Artificial Intelligence (402 citations), Statistics and Probability (67 citations) and Computational Theory and Mathematics (74 citations). Ming-Shong Lan has collaborated with scholars based in United States and Japan. Frequent co-authors include Shigeo Abe, Victor N. Uebele, David Dornfeld, Ruck Thawonmas, Po Ting Lin and Tennyson Smith. Their work appears in journals such as IEEE Transactions on Fuzzy Systems, Journal of Tribology 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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