Hao Quan

2.4k total citations · 1 hit paper
54 papers, 1.9k citations indexed

About

Hao Quan is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Hao Quan has authored 54 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Electrical and Electronic Engineering, 16 papers in Artificial Intelligence and 8 papers in Control and Systems Engineering. Recurrent topics in Hao Quan's work include Energy Load and Power Forecasting (24 papers), Solar Radiation and Photovoltaics (15 papers) and Electric Power System Optimization (14 papers). Hao Quan is often cited by papers focused on Energy Load and Power Forecasting (24 papers), Solar Radiation and Photovoltaics (15 papers) and Electric Power System Optimization (14 papers). Hao Quan collaborates with scholars based in China, Singapore and Australia. Hao Quan's co-authors include Dipti Srinivasan, Abbas Khosravi, Wenjie Zhang, Dazhi Yang, Ashwin M. Khambadkone, Carlos D. Rodríguez‐Gallegos, Oktoviano Gandhi, Vahid R. Disfani, Licheng Liu and Chin‐Woo Tan and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Applied Energy and IEEE Access.

In The Last Decade

Hao Quan

51 papers receiving 1.9k citations

Hit Papers

Short-Term Load and Wind Power Forecasting Using Neural N... 2013 2026 2017 2021 2013 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals
    2013 503 citations Hao Quan, Dipti Srinivasan et al. IEEE Transactions on Neural Networks and Learning Systems profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hao Quan China 18 1.5k 662 312 261 208 54 1.9k
Mahdi Khodayar United States 18 1.3k 0.9× 711 1.1× 162 0.5× 291 1.1× 126 0.6× 46 1.7k
Yaoyao He China 24 1.2k 0.8× 492 0.7× 396 1.3× 173 0.7× 101 0.5× 76 1.9k
Zi Lin United Kingdom 15 1.3k 0.9× 588 0.9× 179 0.6× 332 1.3× 92 0.4× 31 1.9k
Muhammad Qamar Raza Australia 14 1.4k 0.9× 789 1.2× 237 0.8× 259 1.0× 496 2.4× 28 1.7k
Hui Jiang China 22 1.6k 1.1× 654 1.0× 142 0.5× 579 2.2× 240 1.2× 94 2.2k
Xiwei Mi China 18 1.7k 1.1× 751 1.1× 351 1.1× 243 0.9× 100 0.5× 29 2.2k
H.M.I. Pousinho Portugal 28 1.9k 1.3× 546 0.8× 261 0.8× 317 1.2× 149 0.7× 55 2.3k
Lambros Ekonomou Greece 23 1.5k 1.0× 262 0.4× 382 1.2× 525 2.0× 197 0.9× 88 2.0k
S.J.P.S. Mariano Portugal 25 1.6k 1.1× 472 0.7× 214 0.7× 293 1.1× 488 2.3× 122 2.1k
Minas C. Alexiadis Greece 15 1.7k 1.2× 549 0.8× 161 0.5× 420 1.6× 135 0.6× 36 2.0k

Countries citing papers authored by Hao Quan

Since Specialization
Citations

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

Fields of papers citing papers by Hao Quan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hao Quan

This figure shows the co-authorship network connecting the top 25 collaborators of Hao Quan. A scholar is included among the top collaborators of Hao Quan 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 Hao Quan. Hao Quan 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
1.
Tan, Ming, Chen‐Chen Tan, Xinyu Zhang, et al.. (2025). Sleep quality, APOE ε4, and Alzheimer’s disease: associations from two prospective cohort studies and mechanisms by plasma proteomic analysis. BMC Medicine. 23(1). 462–462. 1 indexed citations
2.
Quan, Hao, et al.. (2024). A deep-learning algorithm with two-stage training for solar forecast post-processing. Solar Energy. 273. 112504–112504. 3 indexed citations
3.
Hu, Dayu, Renxiang Guan, Ke Liang, et al.. (2024). scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data. Briefings in Bioinformatics. 25(6). 7 indexed citations
4.
Quan, Hao, et al.. (2024). Probabilistic assessment method of small-signal stability in power systems based on quantitative PSS analysis. Applied Energy. 375. 124119–124119. 5 indexed citations
5.
6.
Qiu, Zhibin, et al.. (2024). Detection of Defects in Wind Turbin Blade Based on Cascaded Adaptive Hybrid Attention Network. IEEE Access. 12. 99349–99361. 1 indexed citations
7.
Li, Zixiong, et al.. (2023). Transformer fault classification for diagnosis based on DGA and deep belief network. Energy Reports. 9. 250–256. 23 indexed citations
8.
Zheng, Tingting, Song Zheng, Ke Wang, et al.. (2022). Automatic CD30 scoring method for whole slide images of primary cutaneous CD30 + lymphoproliferative diseases. Journal of Clinical Pathology. 76(10). 705–711. 4 indexed citations
9.
10.
Zhang, Zhirui, et al.. (2022). Research on Digital Twins Technology and Its Future Implementation in Transformer Overload Analysis. 136. 490–495. 1 indexed citations
11.
Wang, Tao, et al.. (2021). Conceptual Design of 3-T all HTS MRI Using No-Insulation Winding Technology: Main Split Coil-System and its Active Shield. IEEE Transactions on Applied Superconductivity. 31(8). 1–5. 2 indexed citations
12.
Wang, Tao, et al.. (2021). Conceptual Design of 3-T All HTS MRI Using No-Insulation Winding Technology: Electromagnetic Stress Reinforced Structure. IEEE Transactions on Applied Superconductivity. 31(8). 1–5. 6 indexed citations
13.
Yu, Lisu, et al.. (2021). Wild Animal Information Collection Based on Depthwise Separable Convolution in Software Defined IoT Networks. Electronics. 10(17). 2091–2091. 5 indexed citations
14.
15.
Quan, Hao, Abbas Khosravi, Dazhi Yang, & Dipti Srinivasan. (2019). A Survey of Computational Intelligence Techniques for Wind Power Uncertainty Quantification in Smart Grids. IEEE Transactions on Neural Networks and Learning Systems. 31(11). 4582–4599. 88 indexed citations
16.
Yang, Dazhi, Hao Quan, Vahid R. Disfani, & Licheng Liu. (2017). Reconciling solar forecasts: Geographical hierarchy. Solar Energy. 146. 276–286. 62 indexed citations
17.
Quan, Hao, Dipti Srinivasan, Ashwin M. Khambadkone, & Abbas Khosravi. (2015). A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources. Applied Energy. 152. 71–82. 154 indexed citations
18.
Quan, Hao, Dipti Srinivasan, & Abbas Khosravi. (2014). Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals. IEEE Transactions on Neural Networks and Learning Systems. 26(9). 2123–2135. 85 indexed citations
19.
Quan, Hao, Dipti Srinivasan, & Abbas Khosravi. (2013). Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals. IEEE Transactions on Neural Networks and Learning Systems. 25(2). 303–315. 503 indexed citations breakdown →
20.
Quan, Hao, Dipti Srinivasan, Abbas Khosravi, Saeid Nahavandi, & Doug Creighton. (2013). Construction of neural network-based prediction intervals for short-term electrical load forecasting. National University of Singapore. 9. 66–72. 12 indexed citations

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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