Meng Hu

1.4k citations
77 papers · 784 · h-index 14

Impact in

Papers in

Meng Hu

67 papers receiving 763 citations

Peers

Meng Hu
Comparison fields: 5 of 125
  • Computational Theory and Mathematics 273
  • Building and Construction 110
  • Information Systems 154
  • Artificial Intelligence 204
  • Transportation 39
Replace Pedro J. Zufiria with:
Pedro J. Zufiria Spain
José R. Dorronsoro Spain
Liang Sun China
H. Ichihashi Japan
Zhou Jin China
Juan Zhao China
Roy W. Dobbins United States
Rodrigo Fernandes de Mello Brazil
Russell C. Eberhart United States
Meng Hu relative to Pedro J. Zufiria Spain Pedro J. Zufiria's profile →
Citations per field
00.5×5.2×
Pedro J. Zufiria · 1×
Citations per year

Countries citing papers authored by Meng Hu

Since Specialization
Citations

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

Fields of papers citing papers by Meng Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Meng Hu, 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 Meng Hu Line = papers co-authored together Meng Hu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202188
2 201973
3 202170
4 201465
5 201954
6 201548
7 202138
8 201931
9 201625
10 201825
11 202321
12 202115
13 201214
14 201413
15 202412
16 201110
17 202210
18 201210
19
Rolling Bearing Fault Diagnosis Method Based on LMD Multi-scale Entropy and Probabilistic Neural Network
20169
20
Triple positive solutions for an impulsive dynamic equation with integral boundary condition on time scales
20139

About Meng Hu

Meng Hu is a scholar working on Computational Theory and Mathematics, Applied Mathematics, Artificial Intelligence, Numerical Analysis and Control and Systems Engineering, having authored 77 papers that have together received 784 indexed citations. Recurring topics across this work include Nonlinear Differential Equations Analysis (16 papers), Rough Sets and Fuzzy Logic (13 papers), Differential Equations and Numerical Methods (9 papers), Data Mining Algorithms and Applications (8 papers), Fractional Differential Equations Solutions (6 papers), Mathematical and Theoretical Epidemiology and Ecology Models (5 papers), Neural Networks and Applications (4 papers) and Differential Equations and Boundary Problems (3 papers). The work is most often cited by research in Computational Theory and Mathematics (273 citations), Building and Construction (110 citations), Information Systems (154 citations), Artificial Intelligence (204 citations) and Transportation (39 citations). Meng Hu has collaborated with scholars based in China, Macao and United States. Frequent co-authors include Eric C.C. Tsang, Yanting Guo, Weihua Xu, Degang Chen, Jiawei Zhan, Jiyao An, Werner Brack, Weihong Chen, Jan Liebetrau and Hualou Liang. Their work appears in journals such as Knowledge-Based Systems, Advances in Difference Equations, Information Sciences, Measurement and Analytical and Bioanalytical Chemistry.

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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