Yiliao Song

1.5k citations
32 papers · 1.1k indexed · h-index 17
Topics
Data Stream Mining Techniques (16 papers)Machine Learning and Data Classification (11 papers)Energy Load and Power Forecasting (6 papers)
Partner nations
AustraliaChinaCanada

In The Last Decade

Yiliao Song

31 papers receiving 1.1k citations

Peers

Yiliao Song
Comparison fields: 5 of 103
  • Artificial Intelligence 494
  • Electrical and Electronic Engineering 481
  • Management Science and Operations Research 212
  • Environmental Engineering 171
  • Building and Construction 104
Replace Chengqing Yu with:
Chengqing Yu China
Paulo S. G. de Mattos Neto Brazil
Emilio G. Ortiz‐García Spain
Ángel M. Pérez‐Bellido Spain
Hongmin Li China
Guo‐Feng Fan Taiwan
Hansika Hewamalage Australia
Roberto Corizzo United States
Xueheng Qiu Singapore
Ali Fiaz United Arab Emirates
Yiliao Song relative to Chengqing Yu China Chengqing Yu's profile →
Citations per field
00.5×20×40×60×84×
Chengqing Yu · 1×
Citations per year

Countries citing papers authored by Yiliao Song

Since Specialization
Citations

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

Fields of papers citing papers by Yiliao Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yiliao Song

This figure shows the co-authorship network connecting the top 25 collaborators of Yiliao Song. A scholar is included among the top collaborators of Yiliao Song 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 Yiliao Song. Yiliao Song 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 0
2 6
3 4
4 12
5 34
6 18
7 31
8 16
9 28
10 3
11 8
12 60
13 4
14 10
15 23
16 71
17 104
18 9
19 224
20 10

About Yiliao Song

Yiliao Song is a scholar working on Management Science and Operations Research, Artificial Intelligence and Environmental Engineering, having authored 32 papers that have together received 1.1k indexed citations. Recurring topics across this work include Data Stream Mining Techniques (16 papers), Machine Learning and Data Classification (11 papers) and Energy Load and Power Forecasting (6 papers). The work is most often cited by research in Management Science and Operations Research (212 citations), Artificial Intelligence (494 citations) and Environmental Engineering (171 citations). Yiliao Song has collaborated with scholars based in Australia, China and Canada. Frequent co-authors include Feng Liu, Jie Lü, Jianzhou Wang, Guangquan Zhang, Ru Hou, Anjin Liu, Ping Jiang, Shanshan Qin, Haiyan Lu and Jiansheng Qu. Their work appears in journals such as Nano Letters, Renewable and Sustainable Energy Reviews and Atmospheric Environment.

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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