Meng Cheng
- Computational Theory and Mathematics
- Statistics, Probability and Uncertainty
- Civil and Structural Engineering
- Management Science and Operations Research
- Mechanical Engineering
- Co-authors
- Jiexiang HuQi ZhouLeshi ShuPing JiangQuan LinHuaping LiuQian ZhangTianhao Wang
- Topics
- Probabilistic and Robust Engineering Design (2 papers)Advanced Multi-Objective Optimization Algorithms (2 papers)Optimal Experimental Design Methods (2 papers)
- Cited by
- Statistics, Probability and UncertaintyComputational Theory and MathematicsManagement Science and Operations Research
- Journals
- SHILAP Revista de lepidopterologíaConstruction and Building MaterialsStructural and Multidisciplinary Optimization
- Partner nations
- ChinaUnited Kingdom
In The Last Decade
Meng Cheng
5 papers receiving 37 citations
Peers
Comparison fields: 5 of 24
- Computational Theory and Mathematics 20
- Statistics, Probability and Uncertainty 14
- Civil and Structural Engineering 11
- Management Science and Operations Research 7
- Mechanical Engineering 6
Countries citing papers authored by Meng Cheng
This map shows the geographic impact of Meng Cheng'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 Meng Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meng Cheng more than expected).
Fields of papers citing papers by Meng Cheng
This network shows the impact of papers produced by Meng Cheng. 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 Meng Cheng. The network helps show where Meng Cheng may publish in the future.
Co-authorship network of co-authors of Meng Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Meng Cheng. A scholar is included among the top collaborators of Meng Cheng 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 Meng Cheng. Meng Cheng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 10 | |
| 5 | 20 |
About Meng Cheng
Meng Cheng is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research and Computational Theory and Mathematics, having authored 5 papers that have together received 38 indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (2 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Optimal Experimental Design Methods (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (14 citations), Computational Theory and Mathematics (20 citations) and Management Science and Operations Research (7 citations). Meng Cheng has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Jiexiang Hu, Qi Zhou, Leshi Shu, Ping Jiang, Quan Lin, Huaping Liu, Qian Zhang, Tianhao Wang, Rui Qin and Yi Liu. Their work appears in journals such as SHILAP Revista de lepidopterología, Construction and Building Materials and Structural and Multidisciplinary Optimization.
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.