Spatio-temporal prediction and factor identification of urban air quality using support vector machine-Reference-Cited by-同舟云学术

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Spatio-temporal prediction and factor identification of urban air quality using support vector machine

Published:2022-01 Issue: Volume:41 Page:101055
ISSN:2212-0955
Container-title:Urban Climate
language:en
Short-container-title:Urban Climate

Author:

Liu Chih-Chun,Lin Tzu-Chi,Yuan Kuang-Yu,Chiueh Pei-Te

Publisher

Elsevier BV

Subject

Atmospheric Science,Urban Studies,Environmental Science (miscellaneous),Geography, Planning and Development

Reference45 articles.

1. Spatial variation in the association between NO2 concentrations and shipping emissions in the Red Sea;Alahmadi;Sci. Total Environ.,2019

2. SVM aggregation modelling for spatio-temporal air pollution analysis;Ali;IEEE,2014

3. Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe – the ESCAPE project;Beelen;Atmos. Environ.,2013

4. LIBSVM: a library for support vector machines;Chang;ACM Trans. Intell. Syst. Technol. (TIST),2011

5. Traffic and meteorological impacts on near-road air quality: summary of methods and trends from the Raleigh near-road study;Cope;J. Air Waste Manage. Assoc.,2008

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