Yang-Geng Fu

614 total citations
37 papers, 451 citations indexed

About

Yang-Geng Fu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Yang-Geng Fu has authored 37 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 10 papers in Computational Theory and Mathematics and 9 papers in Management Science and Operations Research. Recurrent topics in Yang-Geng Fu's work include Multi-Criteria Decision Making (9 papers), Rough Sets and Fuzzy Logic (9 papers) and Advanced Graph Neural Networks (7 papers). Yang-Geng Fu is often cited by papers focused on Multi-Criteria Decision Making (9 papers), Rough Sets and Fuzzy Logic (9 papers) and Advanced Graph Neural Networks (7 papers). Yang-Geng Fu collaborates with scholars based in China, Hong Kong and United Kingdom. Yang-Geng Fu's co-authors include Ying‐Ming Wang, Long-Hao Yang, Ying-Ming Wang, Kwai‐Sang Chin, Leilei Chang, Qun Su, Genggeng Liu, Longkun Guo, Lei Chen and Longjiang Chen and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Yang-Geng Fu

30 papers receiving 433 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yang-Geng Fu China	13	273	119	114	84	47	37	451
P. Vannoorenberghe France	7	292 1.1×	124 1.0×	183 1.6×	75 0.9×	70 1.5×	24	504
Pedro Villar Spain	13	492 1.8×	133 1.1×	166 1.5×	87 1.0×	23 0.5×	21	659
Shenglei Chen China	9	272 1.0×	46 0.4×	50 0.4×	94 1.1×	35 0.7×	24	443
Ivona Brajević Serbia	13	355 1.3×	163 1.4×	96 0.8×	28 0.3×	77 1.6×	23	586
Raja Marappan India	13	209 0.8×	46 0.4×	59 0.5×	151 1.8×	47 1.0×	55	589
Khalil El Hindi Saudi Arabia	15	273 1.0×	51 0.4×	53 0.5×	134 1.6×	42 0.9×	42	477
Jerry Swan United Kingdom	13	303 1.1×	139 1.2×	113 1.0×	57 0.7×	30 0.6×	47	522
Shafaatunnur Hasan Malaysia	12	428 1.6×	70 0.6×	33 0.3×	93 1.1×	100 2.1×	38	659
Xuyan Tu China	11	206 0.8×	68 0.6×	36 0.3×	51 0.6×	65 1.4×	107	439
Hongwu Qin China	17	213 0.8×	340 2.9×	444 3.9×	115 1.4×	44 0.9×	91	823

Countries citing papers authored by Yang-Geng Fu

Since Specialization

Citations

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

Fields of papers citing papers by Yang-Geng Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yang-Geng Fu

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

All Works

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20 of 20 papers shown

Fang, Weijie, Yang-Geng Fu, Jiaquan Gao, et al.. (2025). Acceleration of Timing-Aware Gate-Level Logic Simulation Through One-Pass GPU Parallelism. IEEE Transactions on Computers. 74(8). 2675–2686.

Fu, Yang-Geng, et al.. (2024). FE-CFNER: Feature Enhancement-based approach for Chinese Few-shot Named Entity Recognition. Computer Speech & Language. 90. 101730–101730. 3 indexed citations

Li, Jin, et al.. (2024). Enhanced Graph Transformer: Multi-scale attention with Heterophilous Curriculum Augmentation. Knowledge-Based Systems. 309. 112874–112874.

Ye, Qingqing, et al.. (2024). DWSSA: Alleviating over-smoothness for deep Graph Neural Networks. Neural Networks. 174. 106228–106228. 9 indexed citations

Fu, Yang-Geng, et al.. (2024). GSSCL: A framework for Graph Self-Supervised Curriculum Learning based on clustering label smoothing. Neural Networks. 181. 106787–106787. 5 indexed citations

Ye, Qingqing, et al.. (2024). Boosting Accuracy of Differentially Private Continuous Data Release for Federated Learning. IEEE Transactions on Information Forensics and Security. 19. 10287–10301.

Xu, Shuling, et al.. (2024). Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-Smoothness in Deep GNNs. Proceedings of the AAAI Conference on Artificial Intelligence. 38(12). 13528–13536.

Li, Jin, et al.. (2024). LightCapsGNN: light capsule graph neural network for graph classification. Knowledge and Information Systems. 66(10). 6363–6386. 1 indexed citations

Fu, Yang-Geng, et al.. (2023). M-Sim: Multi-level Semantic Inference Model for Chinese short answer scoring in low-resource scenarios. Computer Speech & Language. 84. 101575–101575.

10.

Fu, Yang-Geng, et al.. (2023). Disjunctive belief rule-based reasoning for decision making with incomplete information. Information Sciences. 625. 49–64. 18 indexed citations

11.

Fu, Yang-Geng, et al.. (2023). CogNLG: Cognitive graph for KG‐to‐text generation. Expert Systems. 41(1). 3 indexed citations

12.

Fu, Yang-Geng, et al.. (2021). Construction of EBRB classifier for imbalanced data based on Fuzzy C-Means clustering. Knowledge-Based Systems. 234. 107590–107590. 27 indexed citations

13.

Fu, Yang-Geng, et al.. (2021). EBRB cascade classifier for imbalanced data via rule weight updating. Knowledge-Based Systems. 223. 107010–107010. 25 indexed citations

14.

Chen, Nannan, et al.. (2021). Random clustering forest for extended belief rule-based system. Soft Computing. 25(6). 4609–4619. 17 indexed citations

15.

Guan, Yu, et al.. (2021). Belief-Rule-Base Inference Method Based on Gradient Descent With Momentum. IEEE Access. 9. 34487–34499. 15 indexed citations

16.

Yang, Long-Hao, Ying-Ming Wang, Leilei Chang, & Yang-Geng Fu. (2017). A disjunctive belief rule-based expert system for bridge risk assessment with dynamic parameter optimization model. Computers & Industrial Engineering. 113. 459–474. 34 indexed citations

17.

Liu, Wanling, et al.. (2016). Belief rule based inference methodology for classification based on differential evolution algorithm. 46(9). 773. 1 indexed citations

18.

Fu, Yang-Geng, et al.. (2016). GDA Based Ensemble Learning Methods for Parameter Training in Belief Rule Base. 10(12). 1661. 3 indexed citations

19.

Yang, Long-Hao, Ying-Ming Wang, Qun Su, Yang-Geng Fu, & Kwai‐Sang Chin. (2016). Multi-attribute search framework for optimizing extended belief rule-based systems. Information Sciences. 370-371. 159–183. 46 indexed citations

20.

Fu, Yang-Geng, et al.. (2012). An Evidential Reasoning Approach for College Students' Autonomous Learning Ability Evaluation. 2. 410–414.

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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