Rui Tang

1.0k total citations
44 papers, 675 citations indexed

About

Rui Tang is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computational Theory and Mathematics. According to data from OpenAlex, Rui Tang has authored 44 papers receiving a total of 675 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 6 papers in Computational Theory and Mathematics. Recurrent topics in Rui Tang's work include Metaheuristic Optimization Algorithms Research (14 papers), Evolutionary Algorithms and Applications (8 papers) and Advanced Multi-Objective Optimization Algorithms (6 papers). Rui Tang is often cited by papers focused on Metaheuristic Optimization Algorithms Research (14 papers), Evolutionary Algorithms and Applications (8 papers) and Advanced Multi-Objective Optimization Algorithms (6 papers). Rui Tang collaborates with scholars based in China, Macao and Australia. Rui Tang's co-authors include Simon Fong, Suash Deb, Xin‐She Yang, Raymond K. Wong, Joanna M. Biernacka, Mariza de Andrade, Yan Zhong, Yuhao Chen, Xinyu Luo and Jason P. Sinnwell and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Rui Tang

42 papers receiving 636 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rui Tang China 15 328 87 79 68 60 44 675
Satish Chandra India 13 202 0.6× 73 0.8× 92 1.2× 76 1.1× 67 1.1× 45 541
Andrea Bommert Germany 4 251 0.8× 51 0.6× 97 1.2× 31 0.5× 121 2.0× 8 583
Yuhai Zhao China 16 421 1.3× 141 1.6× 152 1.9× 85 1.3× 134 2.2× 95 790
Changcheng Huang Canada 11 375 1.1× 74 0.9× 78 1.0× 150 2.2× 32 0.5× 22 745
Sławomir T. Wierzchoń Poland 15 256 0.8× 60 0.7× 71 0.9× 48 0.7× 32 0.5× 44 597
Jinfang Sheng China 17 190 0.6× 91 1.0× 63 0.8× 177 2.6× 53 0.9× 73 830
Xiaoyue Feng China 16 618 1.9× 303 3.5× 166 2.1× 82 1.2× 148 2.5× 46 1.1k
Utkarsh Mahadeo Khaire India 7 251 0.8× 37 0.4× 92 1.2× 38 0.6× 75 1.3× 13 516
Ranjit Panigrahi India 12 336 1.0× 83 1.0× 86 1.1× 223 3.3× 25 0.4× 27 732
Jinze Liu China 11 265 0.8× 66 0.8× 83 1.1× 27 0.4× 38 0.6× 47 489

Countries citing papers authored by Rui Tang

Since Specialization
Citations

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

Fields of papers citing papers by Rui Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rui Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Rui Tang. A scholar is included among the top collaborators of Rui Tang 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 Rui Tang. Rui Tang 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.
Chen, Hongsheng, Tengfei Zhang, Changheui Jang, et al.. (2023). Microstructures, tensile properties and corrosion behaviors of Fe20Cr25NiNb stainless steels with different Al contents in supercritical carbon dioxide. Journal of Materials Research and Technology. 23. 5246–5259. 6 indexed citations
2.
Yang, Liuyang, Zhimin Liu, Rui Tang, et al.. (2023). SAR model for accurate detection of multi-label arrhythmias from electrocardiograms. Heliyon. 9(11). e21627–e21627. 1 indexed citations
3.
Tang, Rui, et al.. (2023). Distributed Particle Filter Based on Particle Exchanges. Research Repository (Delft University of Technology). 1–8. 3 indexed citations
4.
Tang, Rui, et al.. (2023). GAN-inspired Intelligent Jamming and Anti-jamming Strategy for Semantic Communication Systems. 1623–1628. 10 indexed citations
5.
Zhang, Weiya, et al.. (2022). Approximate inferring with confidence predicting based on uncertain knowledge graph embedding. Information Sciences. 609. 679–690. 14 indexed citations
6.
Luo, Xinyu, Liuyang Yang, Hongyu Cai, et al.. (2021). Multi-classification of arrhythmias using a HCRNet on imbalanced ECG datasets. Computer Methods and Programs in Biomedicine. 208. 106258–106258. 43 indexed citations
7.
Yang, Jie, Simon Fong, Han Wang, et al.. (2021). Artificial intelligence in ophthalmopathy and ultra-wide field image: A survey. Expert Systems with Applications. 182. 115068–115068. 23 indexed citations
8.
Lan, Kun, Gloria Li, Jie Yang, et al.. (2021). Convolutional neural network with group theory and random selection particle swarm optimizer for enhancing cancer image classification. Mathematical Biosciences & Engineering. 18(5). 5573–5591. 7 indexed citations
9.
Lan, Kun, Liansheng Liu, Yuhao Chen, et al.. (2020). Multi-view convolutional neural network with leader and long-tail particle swarm optimizer for enhancing heart disease and breast cancer detection. Neural Computing and Applications. 32(19). 15469–15488. 16 indexed citations
10.
Zhang, Weiya, et al.. (2020). Fast Confidence Prediction of Uncertainty based on Knowledge Graph Embedding. 1–6. 3 indexed citations
11.
Deb, Suash, Zhonghuan Tian, Simon Fong, et al.. (2018). Solving permutation flow-shop scheduling problem by rhinoceros search algorithm. Soft Computing. 22(18). 6025–6034. 13 indexed citations
12.
Li, Zhen, Donghui Wen, Yue Ma, et al.. (2018). Prediction of alloy composition and microhardness by random forest in maraging stainless steels based on a cluster formula. Journal of Iron and Steel Research International. 25(7). 717–723. 10 indexed citations
13.
Tang, Rui, Simon Fong, Nilanjan Dey, Raymond K. Wong, & Sabah Mohammed. (2017). Cross Entropy Method Based Hybridization of Dynamic Group Optimization Algorithm. Entropy. 19(10). 533–533. 11 indexed citations
14.
Fong, Simon, Yan Zhuang, Rui Tang, Xin‐She Yang, & Suash Deb. (2013). Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search. Journal of Applied Mathematics. 2013. 1–18. 17 indexed citations
15.
Tang, Rui, et al.. (2013). Multi-Objective Optimization Algorithms Design based on Support Vector Regression Metamodeling. TELKOMNIKA Indonesian Journal of Electrical Engineering. 11(11). 1 indexed citations
16.
Sha, Qiuying, Rui Tang, & Shuanglin Zhang. (2009). Detecting susceptibility genes for rheumatoid arthritis based on a novel sliding-window approach. BMC Proceedings. 3(S7). S14–S14. 5 indexed citations
17.
Tang, Rui, Jason P. Sinnwell, Jia Li, et al.. (2009). Identification of genes and haplotypes that predict rheumatoid arthritis using random forests. BMC Proceedings. 3(S7). S68–S68. 27 indexed citations
18.
Tang, Rui, Tao Feng, Qiuying Sha, & Shuanglin Zhang. (2009). A Variable‐Sized Sliding‐Window Approach for Genetic Association Studies via Principal Component Analysis. Annals of Human Genetics. 73(6). 631–637. 19 indexed citations
19.
Li, Jia, Rui Tang, Joanna M. Biernacka, & Mariza de Andrade. (2009). Identification of gene-gene interaction using principal components. BMC Proceedings. 3(S7). S78–S78. 13 indexed citations
20.
Tang, Rui. (2007). Distributed mining of similarities of outlier patterns. Computer Engineering and Applications Journal.

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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