Xiaohong Guan

536 papers receiving 11.1k citations

Xiaohong Guan's Hit Papers

A Review of Deep Reinforcement Learning for Smart Building Energy Management 2021 · 270 citations
2700+1+3Years since publication50100150200250

Peers

Xiaohong Guan
Comparison fields: 5 of 166
  • Energy Engineering and Power Technology 664
  • Control and Systems Engineering 2.9k
  • Electrical and Electronic Engineering 6.5k
  • Computer Networks and Communications 2.3k
  • Signal Processing 1.1k
Replace Junhua Zhao with:
Junhua Zhao China
Haibo He United States
Nadeem Javaid Pakistan
Tao Yu China
Dipti Srinivasan Singapore
Lingfeng Wang United States
Zhiwu Li China
Noradin Ghadimi Iran
Abdullah Abusorrah Saudi Arabia
Pierluigi Siano Italy
Xiaohong Guan relative to Junhua Zhao China Junhua Zhao's profile →
Citations per field
00.5×5.8×
Junhua Zhao · 1×
Citations per year

Countries citing papers authored by Xiaohong Guan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaohong Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 569 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010388
2
A Review of Deep Reinforcement Learning for Smart Building Energy Management
Hit paper breakdown →
2021270
3 2020247
4 1992197
5 2008182
6 2012176
7 2013163
8 2017150
9 2010142
10 1995132
11 2020122
12 2013119
13 1994115
14 2015114
15 2017111
16 1993111
17 2018109
18 2004109
19 2002106
20 2022100

About Xiaohong Guan

Xiaohong Guan is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Control and Systems Engineering and Information Systems, having authored 569 papers that have together received 11.5k indexed citations. Recurring topics across this work include Smart Grid Energy Management (116 papers), Electric Power System Optimization (86 papers), Network Security and Intrusion Detection (76 papers), Optimal Power Flow Distribution (71 papers), Complex Network Analysis Techniques (63 papers), Internet Traffic Analysis and Secure E-voting (49 papers), Microgrid Control and Optimization (48 papers) and Advanced Malware Detection Techniques (41 papers). The work is most often cited by research in Energy Engineering and Power Technology (664 citations), Control and Systems Engineering (2.9k citations), Electrical and Electronic Engineering (6.5k citations), Computer Networks and Communications (2.3k citations) and Signal Processing (1.1k citations). Xiaohong Guan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhanbo Xu, Qing‐Shan Jia, Qiaozhu Zhai, Chao Shen, Jiang Wu, Peter B. Luh, Feng Gao, Ting Liu, Zhongmin Cai and Liang Yu. Their work appears in journals such as IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, Information Sciences and IEEE Transactions on Knowledge and Data Engineering.

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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