HISYCOL a hybrid computational intelligence system for combined machine learning: the case of air pollution modeling in Athens

2015 ◽  
Vol 27 (5) ◽  
pp. 1191-1206 ◽  
Author(s):  
Ilias Bougoudis ◽  
Konstantinos Demertzis ◽  
Lazaros Iliadis
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Computational Intelligence ◽  
Air Pollution Modeling ◽  
Intelligence System ◽  
Pollution Modeling

OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning

2020 ◽  
Vol 233 ◽  
pp. 117535 ◽  
Author(s):  
Florian Lautenschlager ◽  
Martin Becker ◽  
Konstantin Kobs ◽  
Michael Steininger ◽  
Padraig Davidson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Air Pollution Modeling ◽  
Pollution Modeling

scholarly journals Machine Learning Methods Performance Evaluation*

2021 ◽  
Vol 12 (2) ◽  
pp. 2664-2666
Author(s):  
Zakoldaev D. A., Et. al.
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Performance Evaluation ◽  
Learning Methods ◽  
Air Pollution Modeling ◽  
Machine Learning Methods ◽  
Pollution Modeling ◽  
Evaluation Approaches ◽  
Monitoring Area

In this paper, we describe an approach for air pollution modeling in the data incompleteness scenarios, when the sensors cover the monitoring area only partially. The fundamental calculus and metrics of using machine learning modeling algorithms are presented. Moreover, the assessing indicators and metrics for machine learning methods performance evaluation are described. Based on the conducted analysis, conclusions on the most appropriate evaluation approaches are made.

Photochemical Air Pollution Modeling

2009 ◽  
pp. 269-285
Author(s):  
Carlos Borrego ◽  
Ana Miranda ◽  
Joana Ferreira
Keyword(s):  
Air Pollution ◽  
Air Pollution Modeling ◽  
Pollution Modeling
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