Ruobin Gao
Impact in
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- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
- Environmental Engineering top 5%
Papers in
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- Neural Networks and Applications 7
- Machine Learning and ELM 6
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- Stock Market Forecasting Methods 10
- Forecasting Techniques and Applications 9
- Co-authors
- Ponnuthurai Nagaratnam Suganthan (34 shared papers)Kum Fai Yuen (23 shared papers)Liang Du (10 shared papers)Ruilin Li (10 shared papers)David Z.W. Wang (3 shared papers)Okan Duru (4 shared papers)Minghui Hu (8 shared papers)M. Tanveer (4 shared papers)
In The Last Decade
Ruobin Gao
54 papers receiving 1.3k citations
Ruobin Gao's Hit Papers
Peers
Comparison fields: 5 of 104
- Management Science and Operations Research 264
- Environmental Engineering 214
- Artificial Intelligence 392
- Signal Processing 109
- Ocean Engineering 153
Countries citing papers authored by Ruobin Gao
This map shows the geographic impact of Ruobin Gao'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 Ruobin Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruobin Gao more than expected).
Fields of papers citing papers by Ruobin Gao
This network shows the impact of papers produced by Ruobin Gao. 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 Ruobin Gao. The network helps show where Ruobin Gao may publish in the future.
Co-authors
The 25 scholars most cited alongside Ruobin Gao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Bayesian optimization based dynamic ensemble for time series forecasting Hit paper breakdown → | 2022 | 164 |
| 2 | Random vector functional link network: Recent developments, applications, and future directions Hit paper breakdown → | 2023 | 114 |
| 3 | 2022 | 83 | |
| 4 | 2021 | 71 | |
| 5 | 2022 | 70 | |
| 6 | 2023 | 65 | |
| 7 | 2021 | 57 | |
| 8 | 2023 | 56 | |
| 9 | 2020 | 48 | |
| 10 | 2023 | 46 | |
| 11 | 2023 | 38 | |
| 12 | 2022 | 37 | |
| 13 | 2022 | 34 | |
| 14 | 2022 | 34 | |
| 15 | 2024 | 33 | |
| 16 | 2020 | 33 | |
| 17 | 2024 | 31 | |
| 18 | 2024 | 29 | |
| 19 | 2023 | 27 | |
| 20 | 2022 | 24 |
About Ruobin Gao
Ruobin Gao is a scholar working on Artificial Intelligence, Management Science and Operations Research, Electrical and Electronic Engineering, Environmental Engineering and Cognitive Neuroscience, having authored 59 papers that have together received 1.3k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (11 papers), Stock Market Forecasting Methods (10 papers), Forecasting Techniques and Applications (9 papers), Maritime Ports and Logistics (8 papers), EEG and Brain-Computer Interfaces (8 papers), Neural Networks and Applications (7 papers), Maritime Transport Emissions and Efficiency (7 papers) and Machine Learning and ELM (6 papers). The work is most often cited by research in Management Science and Operations Research (264 citations), Environmental Engineering (214 citations), Artificial Intelligence (392 citations), Signal Processing (109 citations) and Ocean Engineering (153 citations). Ruobin Gao has collaborated with scholars based in Singapore, Qatar and China. Frequent co-authors include Ponnuthurai Nagaratnam Suganthan, Kum Fai Yuen, Liang Du, Ruilin Li, David Z.W. Wang, Okan Duru, Minghui Hu, M. Tanveer, M. A. Ganaie and A. K. Malik. Their work appears in journals such as Applied Soft Computing, Engineering Applications of Artificial Intelligence, Expert Systems with Applications, Information Sciences and Ocean 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.