Guangming Lang

1.4k total citations
34 papers, 1.1k citations indexed

About

Guangming Lang is a scholar working on Computational Theory and Mathematics, Information Systems and Artificial Intelligence. According to data from OpenAlex, Guangming Lang has authored 34 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computational Theory and Mathematics, 14 papers in Information Systems and 14 papers in Artificial Intelligence. Recurrent topics in Guangming Lang's work include Rough Sets and Fuzzy Logic (31 papers), Data Mining Algorithms and Applications (14 papers) and Multi-Criteria Decision Making (12 papers). Guangming Lang is often cited by papers focused on Rough Sets and Fuzzy Logic (31 papers), Data Mining Algorithms and Applications (14 papers) and Multi-Criteria Decision Making (12 papers). Guangming Lang collaborates with scholars based in China, Canada and Japan. Guangming Lang's co-authors include Duoqian Miao, Mingjie Cai, Hamido Fujita, Yiyu Yao, Qingguo Li, Tian Yang, Qimei Xiao, Huangjian Yi, Xiaonan Li and Zhifei Zhang and has published in prestigious journals such as Information Sciences, IEEE Transactions on Fuzzy Systems and Applied Soft Computing.

In The Last Decade

Guangming Lang

33 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Guangming Lang China 17 922 550 468 378 161 34 1.1k
Keyun Qin China 22 1.3k 1.4× 1.0k 1.8× 582 1.2× 288 0.8× 130 0.8× 129 1.7k
Wei-Zhi Wu China 15 1.1k 1.2× 413 0.8× 574 1.2× 547 1.4× 162 1.0× 34 1.2k
Jesús Medina Spain 23 1.4k 1.5× 646 1.2× 727 1.6× 306 0.8× 367 2.3× 135 1.7k
Nouman Azam Canada 14 587 0.6× 237 0.4× 499 1.1× 301 0.8× 101 0.6× 23 885
Yanhong She China 16 837 0.9× 398 0.7× 306 0.7× 300 0.8× 102 0.6× 36 916
Xiaoyan Zhang China 15 617 0.7× 241 0.4× 312 0.7× 251 0.7× 65 0.4× 62 726
Tareq M. Al-shami Yemen 32 1.8k 1.9× 2.2k 4.0× 242 0.5× 156 0.4× 73 0.5× 158 2.7k
Lech Polkowski Poland 17 1.1k 1.2× 190 0.3× 682 1.5× 585 1.5× 155 1.0× 74 1.3k
Guoping Lin China 18 1.1k 1.2× 325 0.6× 491 1.0× 496 1.3× 106 0.7× 39 1.2k
Suyun Zhao China 14 725 0.8× 184 0.3× 465 1.0× 447 1.2× 67 0.4× 33 906

Countries citing papers authored by Guangming Lang

Since Specialization
Citations

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

Fields of papers citing papers by Guangming Lang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangming Lang

This figure shows the co-authorship network connecting the top 25 collaborators of Guangming Lang. A scholar is included among the top collaborators of Guangming Lang 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 Guangming Lang. Guangming Lang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Zhifei, et al.. (2025). Skin lesion classification with mini-batch sampling and deep metric learning. Applied Soft Computing. 185. 113850–113850.
2.
Lang, Guangming, et al.. (2025). Feasible strategies in three-way conflict analysis with three-valued ratings. International Journal of Approximate Reasoning. 186. 109516–109516. 1 indexed citations
3.
Lang, Guangming, et al.. (2025). Granular-Ball Computing-Based Fuzzy Twin Support Vector Machine for Pattern Classification. IEEE Transactions on Fuzzy Systems. 33(7). 2148–2160. 2 indexed citations
4.
Lang, Guangming, Weiping Ding, Duoqian Miao, Hamido Fujita, & Yiyu Yao. (2024). Trisection-fusion and fusion-trisection methods of three-way conflict analysis with Pythagorean fuzzy information. Applied Soft Computing. 164. 111939–111939. 4 indexed citations
5.
Lang, Guangming, et al.. (2024). A framework of granular-ball generation for classification via granularity tuning. Applied Intelligence. 55(1). 2 indexed citations
6.
Yang, Tian, et al.. (2020). Granular Matrix: A New Approach for Granular Structure Reduction and Redundancy Evaluation. IEEE Transactions on Fuzzy Systems. 28(12). 3133–3144. 40 indexed citations
7.
Li, Xiaonan, et al.. (2020). Conflict analysis based on three-way decision for triangular fuzzy information systems. International Journal of Approximate Reasoning. 132. 88–106. 69 indexed citations
8.
Lang, Guangming, Duoqian Miao, & Hamido Fujita. (2019). Three-Way Group Conflict Analysis Based on Pythagorean Fuzzy Set Theory. IEEE Transactions on Fuzzy Systems. 28(3). 447–461. 195 indexed citations
9.
Lang, Guangming, Qingguo Li, Mingjie Cai, Hamido Fujita, & Hongyun Zhang. (2019). Related families-based methods for updating reducts under dynamic object sets. Knowledge and Information Systems. 60(2). 1081–1104. 16 indexed citations
10.
Lang, Guangming, Mingjie Cai, Hamido Fujita, & Qimei Xiao. (2018). Related families-based attribute reduction of dynamic covering decision information systems. Knowledge-Based Systems. 162. 161–173. 61 indexed citations
11.
Yang, Tian, et al.. (2017). Attribute reduction based on related families of fuzzy covering rough sets. 37. 1–5. 1 indexed citations
12.
Lang, Guangming, Duoqian Miao, Mingjie Cai, & Zhifei Zhang. (2017). Incremental approaches for updating reducts in dynamic covering information systems. Knowledge-Based Systems. 134. 85–104. 34 indexed citations
13.
Xiao, Qimei, Guangming Lang, Wenjun Liu, & Mingjie Cai. (2017). The approximations in rough concept lattice and approximable concept lattice. Journal of Intelligent & Fuzzy Systems. 33(6). 3459–3467. 1 indexed citations
14.
Lang, Guangming, Qingguo Li, Mingjie Cai, & Tian Yang. (2015). Characteristic matrixes-based knowledge reduction in dynamic covering decision information systems. Knowledge-Based Systems. 85. 1–26. 38 indexed citations
15.
Lang, Guangming, et al.. (2015). Homomorphisms Between Covering Approximation Spaces. Fundamenta Informaticae. 138(3). 351–371. 3 indexed citations
16.
Lang, Guangming, et al.. (2015). Homomorphisms-based attribute reduction of dynamic fuzzy covering information systems. International Journal of General Systems. 44(7-8). 791–811. 9 indexed citations
17.
Lang, Guangming, Qingguo Li, Mingjie Cai, Tian Yang, & Qimei Xiao. (2014). Incremental approaches to knowledge reduction based on characteristic matrices. International Journal of Machine Learning and Cybernetics. 8(1). 203–222. 29 indexed citations
18.
Lang, Guangming, Qingguo Li, & Tian Yang. (2013). An incremental approach to attribute reduction of dynamic set-valued information systems. International Journal of Machine Learning and Cybernetics. 5(5). 775–788. 20 indexed citations
19.
Lang, Guangming, et al.. (2012). Discernibility matrix simplification with new attribute dependency functions for incomplete information systems. Knowledge and Information Systems. 37(3). 611–638. 12 indexed citations
20.
Lang, Guangming & Qingguo Li. (2010). A New Attribute Dependency Function in Information System. 5. 1–4. 1 indexed citations

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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