AGRIS - International System for Agricultural Science and Technology

Unveiling tropospheric ozone by the traditional atmospheric model and machine learning, and their comparison:A case study in hangzhou, China

2019

Feng, Rui | Zheng, Hui-jun | Zhang, An-ran | Huang, Chong | Gao, Han | Ma, Yu-cheng


Bibliographic information
Environmental pollution
Volume 252 Pagination 366 - 378 ISSN 0269-7491
Publisher
Elsevier Ltd
Other Subjects
Multi-layer perceptron; Dewpoint; Direct solar radiation; Volatile organic compounds; Heat island; Feature importance; Recurrent neural network; Wrf-cmaq; Air pollutants; Random forest
Language
English
Type
Text; Journal Article

2024-02-28
MODS
Data Provider
Lookup at Google Scholar
If you notice any incorrect information relating to this record, please contact us at agris@fao.org