Yinglai Liu

416 total citations
17 papers, 273 citations indexed

About

Yinglai Liu is a scholar working on Mechanical Engineering, Mechanics of Materials and Health Information Management. According to data from OpenAlex, Yinglai Liu has authored 17 papers receiving a total of 273 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Mechanical Engineering, 6 papers in Mechanics of Materials and 5 papers in Health Information Management. Recurrent topics in Yinglai Liu's work include Artificial Intelligence in Healthcare (5 papers), Microstructure and Mechanical Properties of Steels (5 papers) and Welding Techniques and Residual Stresses (5 papers). Yinglai Liu is often cited by papers focused on Artificial Intelligence in Healthcare (5 papers), Microstructure and Mechanical Properties of Steels (5 papers) and Welding Techniques and Residual Stresses (5 papers). Yinglai Liu collaborates with scholars based in China, Taiwan and Denmark. Yinglai Liu's co-authors include Shenghan Zhou, Yiyong Xiao, Wenbing Chang, Siyue Zhang, Xueyi Wu, Lei Ma, Yaorong Feng, Jianxun Zhang, Jing Niu and Xuefeng Lu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Remote Sensing.

In The Last Decade

Yinglai Liu

12 papers receiving 255 citations

Peers

Yinglai Liu
Yinglai Liu
Citations per year, relative to Yinglai Liu Yinglai Liu (= 1×) peers Meng-Ju Hsieh

Countries citing papers authored by Yinglai Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yinglai Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yinglai Liu

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

All Works

17 of 17 papers shown
1.
Liu, Yinglai, et al.. (2023). Fracture analysis on the double-head bolt of wind farm. 4–4.
2.
Zhang, Hongbo, et al.. (2022). Effect of local heat treatment on residual stresses in an in-service repair welded pipeline. Materials Testing. 64(9). 1255–1262. 8 indexed citations
3.
Liu, Yinglai, et al.. (2022). Fracture Analysis of Butt Joint Girth Weld of Pipe and Flange. Journal of Physics Conference Series. 2390(1). 12044–12044. 1 indexed citations
4.
Liu, Yinglai, et al.. (2021). Research on the influence of heat treatment temperature on bearing capacity of high steel grade pipeline during in-service welding. SHILAP Revista de lepidopterología. 353. 1020–1020.
5.
Liu, Yinglai, et al.. (2021). Research on Preheating Temperature Field Test of Natural Gas Pipeline in Service Welding under Extreme Condition. SHILAP Revista de lepidopterología. 353. 1001–1001.
7.
Chang, Wenbing, et al.. (2020). Analysis of University Students’ Behavior Based on a Fusion K-Means Clustering Algorithm. Applied Sciences. 10(18). 6566–6566. 21 indexed citations
8.
Chang, Wenbing, et al.. (2019). Prediction model of stroke recurrence based on support vector machine. Journal of Physics Conference Series. 1324(1). 12095–12095. 1 indexed citations
9.
Chang, Wenbing, et al.. (2019). A Machine-Learning-Based Prediction Method for Hypertension Outcomes Based on Medical Data. Diagnostics. 9(4). 178–178. 128 indexed citations
10.
Chang, Wenbing, et al.. (2019). A New Hybrid XGBSVM Model: Application for Hypertensive Heart Disease. IEEE Access. 7. 175248–175258. 41 indexed citations
11.
Zhou, Shenghan, et al.. (2019). Text Similarity Measurement of Semantic Cognition Based on Word Vector Distance Decentralization With Clustering Analysis. IEEE Access. 7. 107247–107258. 16 indexed citations
12.
Liu, Yinglai, et al.. (2019). Effect of cross-section distortion on the performance of small-radius induction bends. Natural Gas Industry B. 6(1). 51–57.
13.
Chang, Wenbing, Yinglai Liu, Yiyong Xiao, et al.. (2019). Probability Analysis of Hypertension-Related Symptoms Based on XGBoost and Clustering Algorithm. Applied Sciences. 9(6). 1215–1215. 16 indexed citations
14.
Zhang, Siyue, et al.. (2019). An Effectiveness Evaluation Model for Satellite Observation and Data-Downlink Scheduling Considering Weather Uncertainties. Remote Sensing. 11(13). 1621–1621. 13 indexed citations
15.
Liu, Yinglai, et al.. (2011). Microstructure and Properties of X80 Steels Thick Plate after Different Quenching and Tempering Treatments. 35(6). 16–19. 1 indexed citations
16.
Niu, Jing, et al.. (2009). Tempering microstructure and mechanical properties of pipeline steel X80. Transactions of Nonferrous Metals Society of China. 19. s573–s578. 22 indexed citations
17.
Liu, Yinglai. (2005). Study on Material Selection for High Strength Induction Heating Bend Pipe Used in West to East Gas Pipeline Project.

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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