Xueguan Song

5.9k total citations · 1 hit paper
219 papers, 4.5k citations indexed

About

Xueguan Song is a scholar working on Mechanical Engineering, Civil and Structural Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Xueguan Song has authored 219 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Mechanical Engineering, 59 papers in Civil and Structural Engineering and 58 papers in Computational Theory and Mathematics. Recurrent topics in Xueguan Song's work include Advanced Multi-Objective Optimization Algorithms (55 papers), Probabilistic and Robust Engineering Design (46 papers) and Hydraulic and Pneumatic Systems (35 papers). Xueguan Song is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (55 papers), Probabilistic and Robust Engineering Design (46 papers) and Hydraulic and Pneumatic Systems (35 papers). Xueguan Song collaborates with scholars based in China, United Kingdom and South Korea. Xueguan Song's co-authors include Maolin Shi, Sun We, Chao Zhang, Liye Lv, Bing Ji, Wei Sun, Yihua Hu, Guangyong Sun, Qing Li and Volker Pickert and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Industrial Electronics and Applied Energy.

In The Last Decade

Xueguan Song

197 papers receiving 4.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Recurrent neural networks for real-time prediction of TBM operating parameters

2018 239 citations Xueguan Song, Chao Zhang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xueguan Song China	34	1.5k	1.3k	1.3k	609	589	219	4.5k
Sun We China	34	1.8k 1.2×	1.3k 1.0×	384 0.3×	387 0.6×	219 0.4×	285	3.9k
Francisco Chinesta France	39	2.0k 1.3×	908 0.7×	586 0.5×	697 1.1×	569 1.0×	584	7.3k
Jie Liu China	34	1.2k 0.8×	1.6k 1.2×	386 0.3×	474 0.8×	302 0.5×	213	3.9k
Nam Ho Kim United States	38	1.5k 1.0×	1.3k 1.0×	695 0.6×	1.1k 1.8×	740 1.3×	272	5.4k
Chen Yang China	36	745 0.5×	1.2k 1.0×	573 0.5×	699 1.1×	283 0.5×	151	3.6k
Kang Tai Singapore	37	909 0.6×	1.2k 0.9×	496 0.4×	380 0.6×	889 1.5×	176	4.2k
Zhen Hu United States	35	805 0.5×	1.1k 0.8×	585 0.5×	465 0.8×	1.0k 1.7×	228	4.6k
Pingfeng Wang United States	33	809 0.5×	1.1k 0.9×	803 0.6×	1.5k 2.5×	676 1.1×	222	4.8k
Michael D. Todd United States	40	1.4k 0.9×	3.2k 2.4×	1.2k 1.0×	749 1.2×	89 0.2×	297	5.7k
E. Rank Germany	48	1.2k 0.8×	821 0.6×	1.1k 0.9×	318 0.5×	854 1.4×	298	8.0k

Countries citing papers authored by Xueguan Song

Since Specialization

Citations

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

Fields of papers citing papers by Xueguan Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xueguan Song

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Zheng, Fengjie, et al.. (2025). Sensitivity computational-fluid-dynamics analysis on the damping performance of a hydro-pneumatic spring damper system. Physics of Fluids. 37(9). 1 indexed citations

Li, Yan, Xiaoxun Ma, Xiaodong Miao, et al.. (2024). Numerical investigation and rapid prediction of the erosion rate of gate valve in gas-solid flow. Powder Technology. 448. 120285–120285. 1 indexed citations

He, Xiwang, et al.. (2024). PSDM: A parametrized structural dynamic modeling method based on digital twin for performance prediction. Engineering Structures. 316. 118582–118582. 2 indexed citations

Lai, Xiaonan, et al.. (2024). A pointwise ensemble surrogate based on local optimal surrogate. Information Sciences. 696. 121752–121752. 5 indexed citations

Pang, Yong, Shuai Zhang, Yaochu Jin, et al.. (2024). Surrogate information transfer and fusion in high-dimensional expensive optimization problems. Swarm and Evolutionary Computation. 88. 101586–101586. 5 indexed citations

Pang, Yong, et al.. (2024). Co-design of an unmanned cable shovel for structural and control integrated optimization: A highly heterogeneous constrained multi-objective optimization algorithm. Applied Energy. 376. 124325–124325. 6 indexed citations

Li, Xiping, et al.. (2024). Based on the combination of fluid–solid interaction mechanism model and surrogate model for peristaltic pump performance analysis and multi-objective optimization design. Advanced Engineering Informatics. 62. 102675–102675. 11 indexed citations

Zuo, Luo, Tat‐Soon Yeo, Bo Lu, et al.. (2024). Multifrequency Coherent Integration Target Detection Algorithm for Passive Bistatic Radar. IEEE Transactions on Aerospace and Electronic Systems. 60(5). 6346–6362. 2 indexed citations

Zhang, Shuai, Yong Pang, Qingye Li, Kunpeng Li, & Xueguan Song. (2024). Multi-type data fusion via transfer learning surrogate modeling and its engineering application. Information Sciences. 677. 120918–120918.

10.

Pang, Yong, et al.. (2023). Surrogate-assisted expensive constrained Bi-objective optimization with highly heterogeneous evaluations. Swarm and Evolutionary Computation. 83. 101401–101401. 4 indexed citations

11.

Liu, Zongqi, Xueguan Song, Chao Zhang, Yunsheng Ma, & Dacheng Tao. (2023). RSAL-iMFS: A framework of randomized stacking with active learning for incremental multi-fidelity surrogate modeling. Engineering Applications of Artificial Intelligence. 120. 105871–105871. 7 indexed citations

12.

Xing, Lei, et al.. (2023). A novel flow field design method for HT-PEM fuel cells: a hybrid topology and surrogate model. International Journal of Hydrogen Energy. 48(84). 32955–32967. 10 indexed citations

13.

Zhang, Shuai, et al.. (2023). Recursive surrogate model based on generalized regression neural network. Applied Soft Computing. 145. 110576–110576. 8 indexed citations

14.

Song, Xueguan, et al.. (2023). DADOS: A Cloud-based Data-driven Design Optimization System. Chinese Journal of Mechanical Engineering. 36(1). 5 indexed citations

15.

Liu, Yahua, et al.. (2023). A mechanically durable induction heating coating with desirable anti-/de-icing performance. Surface Engineering. 39(4). 413–420. 2 indexed citations

16.

Wang, Shuo, et al.. (2022). Modified Multifidelity Surrogate Model Based on Radial Basis Function with Adaptive Scale Factor. Chinese Journal of Mechanical Engineering. 35(1). 12 indexed citations

17.

He, Xiwang, et al.. (2021). The biomechanical influence of facet joint parameters on corresponding segment in the lumbar spine: a new visualization method. The Spine Journal. 21(12). 2112–2121. 22 indexed citations

18.

He, Xiwang, Xiaonan Lai, Zhonghai Li, et al.. (2021). Towards a shape-performance integrated digital twin for lumbar spine analysis. 1. 8–8. 24 indexed citations

19.

An, Yi, et al.. (2020). Lightweight Attention Module for Deep Learning on Classification and Segmentation of 3-D Point Clouds. IEEE Transactions on Instrumentation and Measurement. 70. 1–12. 28 indexed citations

20.

Cao, Maosen, Xueguan Song, Wei Xu, Zhongqing Su, & Weidong Zhu. (2014). Performance assessment of natural frequencies in characterizing cracks in beams in noisy conditions. Journal of Vibroengineering. 16(2). 1010–1021. 2 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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