Junhong Liu

501 citations
29 papers · 346 indexed · h-index 9

Junhong Liu

26 papers receiving 329 citations

Peers

Junhong Liu
Comparison fields: 5 of 85
  • Computational Mathematics 6
  • Hardware and Architecture 61
  • Oceanography 46
  • Industrial and Manufacturing Engineering 29
  • Artificial Intelligence 99
Replace Marco Lapegna with:
Marco Lapegna Italy
Yong Jin China
Xiaomin Zhang China
Seungjae Baek South Korea
Dongryeol Lee United States
Yin Wang China
Eduardo R. B. Marques Portugal
Roman Solovyev Russia
Baojun Qiao China
Jianping Xing China
Junhong Liu relative to Marco Lapegna Italy Marco Lapegna's profile →
Citations per field
00.5×6.3×
Marco Lapegna · 1×
Citations per year

Countries citing papers authored by Junhong Liu

Since Specialization
Citations

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

Fields of papers citing papers by Junhong Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20243
2 20241
3 20237
4 20231
5 20233
6 20224
7 20226
8 20218
9 20215
10 20217
11 20205
12 201820
13 201733
14 20137
15
Variable smoothing parameter of the double exponential smoothing forecasting model and its application
20122
16 201044
17
On the differential evolution algorithm and its application to training radial basis function networks
20064
18 20053
19 200513
20 20042

About Junhong Liu

Junhong Liu is a scholar working on Hardware and Architecture, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 346 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (5 papers), Topic Modeling (4 papers), Ionosphere and magnetosphere dynamics (3 papers), Advanced Data Storage Technologies (3 papers), Neural Networks and Applications (3 papers), Metaheuristic Optimization Algorithms Research (3 papers), GNSS positioning and interference (3 papers) and Geophysics and Gravity Measurements (3 papers). The work is most often cited by research in Computational Mathematics (6 citations), Hardware and Architecture (61 citations) and Oceanography (46 citations). Junhong Liu has collaborated with scholars based in China, Finland and United States. Frequent co-authors include Jouni Lampinen, Guangming Tan, Huiyuan Fan, Defeng Gu, Bing Ju, Jia Tu, Jiajia Li, Weifeng Liu, Xin He and Junjie Lai. Their work appears in journals such as Environmental Science & Technology, Molecules and IEEE Transactions on Parallel and Distributed Systems.

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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