NDLI: Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models

Content Provider	Springer Nature Link
Author	KOVAČ ANDRIĆ, ELVIRA SHETA, ALAA FARIS, HOSSAM GAJDOŠIK, MARTINA ŠRAJER
Copyright Year	2016
Abstract	Ozone is one of the most significant secondary pollutants with numerous negative effects on human health and environment including plants and vegetation. Therefore, more effort is made recently by governments and associations to predict ozone concentrations which could help in establishing better plans and regulation for environment protection. In this study, we use two Artificial Neural Network based approaches (MPL and RBF) to develop, for the first time, accurate ozone prediction models, one for urban and another one for rural area in the eastern part of Croatia. The evaluation of actual against the predicted ozone concentrations revealed that MLP and RBF models are very competitive for the training and testing data in the case of Kopački Rit area whereas in the case of Osijek city, MLP shows better evaluation results with 9% improvement in the correlation coefficient. Furthermore, subsequent feature selection process has improved the prediction power of RBF network.
Starting Page	997
Ending Page	1006
Page Count	10
File Format	PDF
ISSN	02534126
Journal	Journal of Earth System Science
Volume Number	125
Issue Number	5
e-ISSN	0973774X
Language	English
Publisher	Springer India
Publisher Date	2016-07-04
Publisher Institution	Indian Academy of Sciences
Publisher Place	New Delhi
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Ozone PM$_{10}$ rural and urban area prediction models artificial neural networks Earth Sciences Extraterrestrial Physics, Space Sciences
Content Type	Text
Resource Type	Article
Subject	1900/1901

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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