KMS Of Academy of mathematics and systems sciences, CAS
| Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis | |
| Li, Yanzhao1; Guo, Ju-e1; Sun, Shaolong1; Li, Jianing2; Wang, Shouyang3,4; Zhang, Chengyuan5 | |
| 2022-03-01 | |
| Source Publication | ENVIRONMENTAL MODELLING & SOFTWARE
 |
| ISSN | 1364-8152 |
| Volume | 149Pages:17 |
| Abstract | Artificial intelligence (AI) techniques have substantially changed the research paradigm in the field of air quality forecasting due to their powerful performance. Considering the improvement in the availability of air quality data and the rapid proliferation of AI techniques, it is necessary to comprehensively and quantitatively review the development of air quality forecasting with AI techniques during the last two decades (2000-2019) by scientometric and content analysis. First, an overview of the relevant countries, institutions, authors, journals, and papers is presented. Then, the research hotspots and frontier evolution are explored by adopting reference co citation analysis and keyword co-occurrence analysis. Furthermore, this study conducts a content analysis to investigate current topical interests to identify research gaps and propose future research directions. The analytical framework and the findings provide helpful insights into the prospects in air quality forecasting with AI techniques. |
| Keyword | Air quality forecasting Artificial intelligence Machine learning Scientometrics Content analysis |
| DOI | 10.1016/j.envsoft.2022.105329 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[71774130] ; National Natural Science Foundation of China[72101197] ; National Natural Science Foundation of China[71988101] ; Fundamental Research Funds for the Central Universities[SK2021007] |
| WOS Research Area | Computer Science ; Engineering ; Environmental Sciences & Ecology ; Water Resources |
| WOS Subject | Computer Science, Interdisciplinary Applications ; Engineering, Environmental ; Environmental Sciences ; Water Resources |
| WOS ID | WOS:000783637900001 |
| Publisher | ELSEVIER SCI LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/60308 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Zhang, Chengyuan |
| Affiliation | 1.Xi An Jiao Tong Univ, Sch Management, Xian 710049, Peoples R China 2.Xi An Jiao Tong Univ, Sch Phys, Xian 710049, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Ctr Forecasting Sci, Beijing 100190, Peoples R China 5.Xidian Univ, Sch Econ & Management, Xian 710071, Peoples R China |
| Recommended Citation GB/T 7714 | Li, Yanzhao,Guo, Ju-e,Sun, Shaolong,et al. Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis[J]. ENVIRONMENTAL MODELLING & SOFTWARE,2022,149:17. |
| APA | Li, Yanzhao,Guo, Ju-e,Sun, Shaolong,Li, Jianing,Wang, Shouyang,&Zhang, Chengyuan.(2022).Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis.ENVIRONMENTAL MODELLING & SOFTWARE,149,17. |
| MLA | Li, Yanzhao,et al."Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis".ENVIRONMENTAL MODELLING & SOFTWARE 149(2022):17. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment