High-resolution mapping of regional VOCs using the enhanced space-time extreme gradient boosting machine (XGBoost) in Shanghai-Reference-Cited by-同舟云学术

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High-resolution mapping of regional VOCs using the enhanced space-time extreme gradient boosting machine (XGBoost) in Shanghai

Published:2023-12 Issue: Volume:905 Page:167054
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Lu Bingqing,Meng Xue,Dong Shanshan,Zhang Zekun,Liu Chao,Jiang Jiakui,Herrmann Hartmut,Li Xiang

Funder

Deutsche Forschungsgemeinschaft

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference70 articles.

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2. A systematic review of land use regression models for volatile organic compounds;Amini;Atmos. Environ.,2017

3. Spatial modelling with Euclidean distance fields and machine learning;Behrens;Eur. J. Soil Sci.,2018

4. Time series prediction of CO2, TVOC and HCHO based on machine learning at different sampling points;Chen;Build. Environ.,2018

5. Xgboost: a scalable tree boosting system;Chen,2016

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