Short-Term Prediction of Carbon Monoxide Concentration Using Artificial Neural Network (NARX) Without Traffic Data: Case Study: Shiraz City-Reference-Cited by-同舟云学术

Short-Term Prediction of Carbon Monoxide Concentration Using Artificial Neural Network (NARX) Without Traffic Data: Case Study: Shiraz City

Published:2018-11-23 Issue:3 Volume:43 Page:533-540
ISSN:2228-6160
Container-title:Iranian Journal of Science and Technology, Transactions of Civil Engineering
language:en
Short-container-title:Iran J Sci Technol Trans Civ Eng

Author:

Mohebbi Mohammad Reza,Karimi Jashni Ayub,Dehghani Maryam^ORCID,Hadad Kamal

Publisher

Springer Science and Business Media LLC

Subject

Geotechnical Engineering and Engineering Geology,Civil and Structural Engineering

Link

http://link.springer.com/content/pdf/10.1007/s40996-018-0210-4.pdf

Reference23 articles.

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3. Brunelli U, Piazza U, Pignato L (2007) Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of Palermo, Italy. Atmos Environ 41:2967–2995

4. Chelani AB, Brerton RG, Walsh PT (1997) Prediction of sulphur dioxide concentration using artificial neural network. Environ Model Softw 17:161–168

5. Diaconescu E (2008) The use of NARX neural networks to predict chaotic time series. Trans Comput Res 3:182–191

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