Liye Lv

792 citations
31 papers · 589 · h-index 14

Impact in

Papers in

Liye Lv

28 papers receiving 583 citations

Peers

Liye Lv
Comparison fields: 5 of 57
  • Statistics, Probability and Uncertainty 209
  • Computational Theory and Mathematics 260
  • Management Science and Operations Research 119
  • Industrial and Manufacturing Engineering 65
  • Civil and Structural Engineering 131
Replace Anoop Mullur with:
Anoop Mullur United States
Jan Griebsch Germany
Ravindra V. Tappeta United States
Brett Wujek United States
Zeping Wu China
Anirban Basudhar United States
Tingli Xie China
I. P. Sobieski United States
Jing Zheng China
Kenneth Moore United States
Liye Lv relative to Anoop Mullur United States Anoop Mullur's profile →
Citations per field
00.5×12.1×
Anoop Mullur · 1×
Citations per year

Countries citing papers authored by Liye Lv

Since Specialization
Citations

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

Fields of papers citing papers by Liye Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Liye Lv, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Liye Lv Line = papers co-authored together Liye Lv links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019130
2 202080
3 201872
4 202343
5 202133
6 201929
7 202023
8 202022
9 202021
10 201819
11 201917
12 201616
13 202215
14 202313
15 20238
16 20247
17 20217
18 20246
19 20236
20 20205

About Liye Lv

Liye Lv is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty, Management Science and Operations Research, Civil and Structural Engineering and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 589 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (17 papers), Optimal Experimental Design Methods (13 papers), Probabilistic and Robust Engineering Design (13 papers), Metaheuristic Optimization Algorithms Research (4 papers), Structural Health Monitoring Techniques (3 papers), Infrastructure Maintenance and Monitoring (2 papers), Robotic Path Planning Algorithms (2 papers) and Advanced Manufacturing and Logistics Optimization (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (209 citations), Computational Theory and Mathematics (260 citations), Management Science and Operations Research (119 citations), Industrial and Manufacturing Engineering (65 citations) and Civil and Structural Engineering (131 citations). Liye Lv has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Xueguan Song, Sun We, Jie Zhang, Maolin Shi, Yongliang Yuan, Lizhang Xu, Jieling Li, Wei Sun, Shuo Wang and Yongliang Yuan. Their work appears in journals such as Structural and Multidisciplinary Optimization, Journal of Mechanical Design, Engineering Optimization, Annals of the New York Academy of Sciences and Engineering Computations.

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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