Skip to content
Publish & Distribute
Publishing Solutions
Distribution Solutions
Library Services
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Journal Matcher
Blog
Contact
Search
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Modelling in Civil Environmental Engineering
Volume 10 (2014): Issue 1 (March 2014)
Open Access
Urban Ozone Concentration Forecasting with Artificial Neural Network in Corsica
Wani Tamas
Wani Tamas
Search for this author on
Sciendo
|
Google Scholar
Tamas, Wani
,
Gilles Notton
Gilles Notton
Search for this author on
Sciendo
|
Google Scholar
Notton, Gilles
,
Christophe Paoli
Christophe Paoli
Search for this author on
Sciendo
|
Google Scholar
Paoli, Christophe
,
Cyril Voyant
Cyril Voyant
Search for this author on
Sciendo
|
Google Scholar
Voyant, Cyril
,
Marie-Laure Nivet
Marie-Laure Nivet
Search for this author on
Sciendo
|
Google Scholar
Nivet, Marie-Laure
and
Aurelia Balu
Aurelia Balu
Search for this author on
Sciendo
|
Google Scholar
Balu, Aurelia
Apr 12, 2014
Modelling in Civil Environmental Engineering
Volume 10 (2014): Issue 1 (March 2014)
About this article
Previous Article
Next Article
Abstract
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Download Cover
Published Online:
Apr 12, 2014
Page range:
29 - 37
DOI:
https://doi.org/10.2478/mmce-2014-0004
Keywords
Air quality forecasting
,
Artificial Neural Network
,
Multilayer Perceptron
,
Ozone concentration
© by Wani Tamas
This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.