Song Ming

26 papers receiving 221 citations

Peers

Song Ming
Comparison fields: 5 of 64
  • Computational Theory and Mathematics 64
  • Information Systems 88
  • Signal Processing 37
  • Media Technology 26
  • Artificial Intelligence 59
Replace Rachid Benslimane with:
Rachid Benslimane Morocco
Markus Götz Germany
Ziyuan Luo China
Jingbo Zhang China
Kang Liu China
Duc Dung Nguyen Vietnam
Yong Zhan United States
Matthieu Cord France
Song Ming relative to Rachid Benslimane Morocco Rachid Benslimane's profile →
Citations per field
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Citations per year

Countries citing papers authored by Song Ming

Since Specialization
Citations

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

Fields of papers citing papers by Song Ming

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200653
2 200645
3 200543
4 199917
5 201916
6 202111
7 19979
8 19988
9 19967
10 19957
11
TECTONIC CONTROL OF THE DABIESHAN OROGENIC BELT OVER THE HEFEI BASIN
20023
12
Design of Synchrotron for Hadron Therapy
20072
13
The Rise Stability of Air-cushion Vehicle
20062
14
Tone Mapping for High Dynamic Range Image Using a Probabilistic Model
20092
15 20212
16 19982
17 20252
18 20231
19
Co-simulation of ACC with ADAMS/CAR and MATLAB
20071
20
The latest understandings of fundamental geology of Jiaonan orogenic belt
20001

About Song Ming

Song Ming is a scholar working on Control and Systems Engineering, Electrical and Electronic Engineering, Biomedical Engineering, Computational Mechanics and Artificial Intelligence, having authored 33 papers that have together received 240 indexed citations. Recurring topics across this work include Hydrocarbon exploration and reservoir analysis (3 papers), Fluid Dynamics and Heat Transfer (3 papers), Electrohydrodynamics and Fluid Dynamics (3 papers), Fluid Dynamics and Mixing (3 papers), Minerals Flotation and Separation Techniques (3 papers), Industrial Technology and Control Systems (3 papers), Innovative Microfluidic and Catalytic Techniques Innovation (2 papers) and Industrial Automation and Control Systems (2 papers). The work is most often cited by research in Computational Theory and Mathematics (64 citations), Information Systems (88 citations), Signal Processing (37 citations), Media Technology (26 citations) and Artificial Intelligence (59 citations). Song Ming has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Sanguthevar Rajasekaran, Artur Steiff, Paul‐Michael Weinspach, Daniel L. Civco, James D. Hurd, Pengfei Li, Xiangang Cao, Yang Liu, Cheng Zeng and Xiaojing Han. Their work appears in journals such as Chemical Engineering Science, IEEE Transactions on Knowledge and Data Engineering, Chemical Engineering and Processing - Process Intensification, Energies and International Journal of Heat and Mass Transfer.

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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