Guojian Zou

792 total citations
18 papers, 556 citations indexed

About

Guojian Zou is a scholar working on Environmental Engineering, Automotive Engineering and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Guojian Zou has authored 18 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Environmental Engineering, 9 papers in Automotive Engineering and 9 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Guojian Zou's work include Air Quality Monitoring and Forecasting (10 papers), Air Quality and Health Impacts (9 papers) and Vehicle emissions and performance (8 papers). Guojian Zou is often cited by papers focused on Air Quality Monitoring and Forecasting (10 papers), Air Quality and Health Impacts (9 papers) and Vehicle emissions and performance (8 papers). Guojian Zou collaborates with scholars based in China, United Kingdom and Australia. Guojian Zou's co-authors include Bo Zhang, Qin Zhao, Jian Yu, Maozhen Li, Jianguo Pan, Yi Rong, Hui Wang, Bo Zhang, Qin Ni and Ye Li and has published in prestigious journals such as The Science of The Total Environment, Atmospheric Environment and Expert Systems with Applications.

In The Last Decade

Guojian Zou

13 papers receiving 541 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guojian Zou China 10 408 320 172 79 70 18 556
Unsok Ryu China 5 319 0.8× 266 0.8× 131 0.8× 78 1.0× 74 1.1× 7 485
Shaolong Cui China 3 417 1.0× 328 1.0× 148 0.9× 94 1.2× 36 0.5× 7 535
Chengzeng You China 3 416 1.0× 328 1.0× 148 0.9× 97 1.2× 34 0.5× 7 507
Yeyun Cai China 9 261 0.6× 208 0.7× 105 0.6× 54 0.7× 23 0.3× 22 493
Samu Varjonen Finland 12 442 1.1× 313 1.0× 180 1.0× 107 1.4× 14 0.2× 25 684
Jane Lin United States 9 206 0.5× 214 0.7× 191 1.1× 40 0.5× 51 0.7× 20 452
Zhiwei Wan China 4 267 0.7× 213 0.7× 101 0.6× 62 0.8× 29 0.4× 7 398
Yi-Ting Tsai Taiwan 9 336 0.8× 260 0.8× 226 1.3× 58 0.7× 21 0.3× 19 645
Hongbin Dai China 13 214 0.5× 183 0.6× 77 0.4× 73 0.9× 17 0.2× 19 554
Huibin Zeng China 13 215 0.5× 184 0.6× 78 0.5× 73 0.9× 16 0.2× 20 465

Countries citing papers authored by Guojian Zou

Since Specialization
Citations

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

Fields of papers citing papers by Guojian Zou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guojian Zou

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

All Works

18 of 18 papers shown
1.
Li, Zhihao, et al.. (2025). Physics-informed deep operator network for traffic state estimation. Transportmetrica B Transport Dynamics. 13(1).
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Ngoduy, Dong, et al.. (2024). Koopman theory meets graph convolutional network: Learning the complex dynamics of non-stationary highway traffic flow for spatiotemporal prediction. Chaos Solitons & Fractals. 187. 115437–115437. 8 indexed citations
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Ngoduy, Dong, et al.. (2024). PI-STGnet: Physics-integrated spatiotemporal graph neural network with fundamental diagram learner for highway traffic flow prediction. Expert Systems with Applications. 258. 125144–125144. 14 indexed citations
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Zou, Guojian, et al.. (2023). A novel spatio-temporal generative inference network for predicting the long-term highway traffic speed. Transportation Research Part C Emerging Technologies. 154. 104263–104263. 19 indexed citations
11.
Zhang, Bo, et al.. (2023). A spatial correlation prediction model of urban PM2.5 concentration based on deconvolution and LSTM. Neurocomputing. 544. 126280–126280. 12 indexed citations
12.
Zhang, Bo, et al.. (2022). Deep learning for air pollutant concentration prediction: A review. Atmospheric Environment. 290. 119347–119347. 113 indexed citations
13.
Zhang, Bo, et al.. (2022). RCL-Learning: ResNet and convolutional long short-term memory-based spatiotemporal air pollutant concentration prediction model. Expert Systems with Applications. 207. 118017–118017. 54 indexed citations
14.
Wang, Ting, Meiting Tu, Ye Li, et al.. (2022). Impact Evaluation of Cyberattacks on Connected and Automated Vehicles in Mixed Traffic Flow and Its Resilient and Robust Control Strategy. Sensors. 23(1). 74–74. 12 indexed citations
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Zhang, Bo, et al.. (2021). A novel Encoder-Decoder model based on read-first LSTM for air pollutant prediction. The Science of The Total Environment. 765. 144507–144507. 80 indexed citations
16.
Zhang, Bo, et al.. (2021). Longer Time Span Air Pollution Prediction: The Attention and Autoencoder Hybrid Learning Model. Mathematical Problems in Engineering. 2021. 1–16. 5 indexed citations
17.
Zou, Guojian, et al.. (2021). FDN-learning: Urban PM2.5-concentration Spatial Correlation Prediction Model Based on Fusion Deep Neural Network. Big Data Research. 26. 100269–100269. 21 indexed citations
18.
Yu, Jian, et al.. (2019). A Novel Combined Prediction Scheme Based on CNN and LSTM for Urban PM2.5 Concentration. IEEE Access. 7. 20050–20059. 206 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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