On the automated learning of air pollution prediction models from data collected by mobile sensor networks

Author(s):  
Pedro Mariano ◽  
Susana Marta Almeida ◽  
Pedro Santana
2015 ◽  
Vol 30 ◽  
pp. e2015010 ◽  
Author(s):  
Youngseob Eum ◽  
Insang Song ◽  
Hwan-Cheol Kim ◽  
Jong-Han Leem ◽  
Sun-Young Kim

2011 ◽  
Vol 66 (3) ◽  
pp. 879-888 ◽  
Author(s):  
A. B. Vicente ◽  
M. M. Jordán ◽  
T. Sanfeliu ◽  
A. Sánchez ◽  
Ma D. Esteban

2020 ◽  
Vol 5 (1) ◽  
pp. 41
Author(s):  
Bambang Endro Yuwono ◽  
Mayang Sari

ABSTRACT As the population grows, the development of the city increases, as a result the movement of transportation also increases. The development of the city can also affect a decrease in green open space. Increased vehicle traffic affects the increase in air pollution. Hence, there is very little research that mathematically connects the influence of traffic volume (passenger car units) and green open space with the level of air pollution. Green open space and the level of air pollution are directly measured on the field. Subsequently, the measurement is calculated by using the regression analysis to obtain a model of the relationship between green open space and traffic volume with the level of air pollution. The research was directly conducted at 3 locations, 2 locations in Jakarta (Semanggi and Tanah Kusir) and 1 location in South Tangerang. This model can be applied to predict that air pollution will occur as a result of traffic volume and the availability of green open space. Keyword: Air pollution, prediction, green open space, traffic volume


2010 ◽  
Vol 21 (3) ◽  
pp. 490-504 ◽  
Author(s):  
Fu-Long XU ◽  
Ming LIU ◽  
Hai-Gang GONG ◽  
Gui-Hai CHEN ◽  
Jian-Ping LI ◽  
...  

2012 ◽  
Vol 23 (3) ◽  
pp. 629-647 ◽  
Author(s):  
Lei WU ◽  
Xiao-Min WANG ◽  
Ming LIU ◽  
Gui-Hai CHEN ◽  
Hai-Gang GONG

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