Qingchun Guo
About
In The Last Decade
Qingchun Guo
41 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 93
- Environmental Engineering 642
- Health, Toxicology and Mutagenesis 444
- Global and Planetary Change 339
- Atmospheric Science 309
- Water Science and Technology 79
Countries citing papers authored by Qingchun Guo
This map shows the geographic impact of Qingchun Guo'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 Qingchun Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingchun Guo more than expected).
Fields of papers citing papers by Qingchun Guo
This network shows the impact of papers produced by Qingchun Guo. 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 Qingchun Guo. The network helps show where Qingchun Guo may publish in the future.
Co-authorship network of co-authors of Qingchun Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Qingchun Guo. A scholar is included among the top collaborators of Qingchun Guo 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 Qingchun Guo. Qingchun Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | A Hybrid Wavelet-Based Deep Learning Model for Accurate Prediction of Daily Surface PM2.5 Concentrations in Guangzhou City breakdown → | 30 |
| 3 | 1 | |
| 4 | Assessing the effectiveness of long short-term memory and artificial neural network in predicting daily ozone concentrations in Liaocheng City breakdown → | 44 |
| 5 | 1 | |
| 6 | 34 | |
| 7 | Comparative Analysis of Multiple Deep Learning Models for Forecasting Monthly Ambient PM2.5 Concentrations: A Case Study in Dezhou City, China breakdown → | 55 |
| 8 | 85 | |
| 9 | 6 | |
| 10 | 44 | |
| 11 | 44 | |
| 12 | 66 | |
| 13 | 7 | |
| 14 | 58 | |
| 15 | 12 | |
| 16 | 4 | |
| 17 | 54 | |
| 18 | 12 | |
| 19 | 41 | |
| 20 | Application of BP neural network model for prediction of water pollutants concentration in Taihu Lake | 3 |
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.