Fang Han

1.6k citations
46 papers · 440 indexed · h-index 13
Topics
Neural dynamics and brain function (30 papers)stochastic dynamics and bifurcation (16 papers)Nonlinear Dynamics and Pattern Formation (10 papers)

In The Last Decade

Fang Han

43 papers receiving 429 citations

Peers

Fang Han
Comparison fields: 5 of 64
  • Cognitive Neuroscience 273
  • Statistical and Nonlinear Physics 205
  • Cellular and Molecular Neuroscience 129
  • Computer Networks and Communications 120
  • Electrical and Electronic Engineering 75
Replace Diogo C. Soriano with:
Diogo C. Soriano Brazil
Peter F. Rowat United States
S. Binczak France
Robert Clewley United States
Yakov Kazanovich Russia
Pengsheng Zheng China
Shenquan Liu China
Toru Aonishi Japan
Lubomir Kostal Czechia
Zhuoqin Yang China
Fang Han relative to Diogo C. Soriano Brazil Diogo C. Soriano's profile →
Citations per field
00.5×2.9×
Diogo C. Soriano · 1×
Citations per year

Countries citing papers authored by Fang Han

Since Specialization
Citations

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

Fields of papers citing papers by Fang Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fang Han

This figure shows the co-authorship network connecting the top 25 collaborators of Fang Han. A scholar is included among the top collaborators of Fang Han 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 Fang Han. Fang Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 1
3 3
4 27
5 7
6 2
7 1
8 1
9 5
10 19
11 5
12 1
13 22
14 2
15 16
16 3
17 1
18 4
19 9
20
Reactive power optimization based on the improved dual population ant colony algorithm
0

About Fang Han

Fang Han is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Cellular and Molecular Neuroscience, having authored 46 papers that have together received 440 indexed citations. Recurring topics across this work include Neural dynamics and brain function (30 papers), stochastic dynamics and bifurcation (16 papers) and Nonlinear Dynamics and Pattern Formation (10 papers). The work is most often cited by research in Statistical and Nonlinear Physics (205 citations), Cognitive Neuroscience (273 citations) and Cellular and Molecular Neuroscience (129 citations). Fang Han has collaborated with scholars based in China, United Kingdom and Denmark. Frequent co-authors include Zhijie Wang, Ying Yu, Qingyun Wang, Marian Wiercigroch, Qingyun Wang, Qishao Lu, Jian‐an Fang, Xiaojuan Sun, Yubo Fan and Guoming Luan. Their work appears in journals such as European Journal of Neuroscience, Neurocomputing and Neural Networks.

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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