Forecasting SO2Pollution Incidents by means of Elman Artificial Neural Networks and ARIMA Models-Reference-Cited by-同舟云学术

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Forecasting SO2Pollution Incidents by means of Elman Artificial Neural Networks and ARIMA Models

Published:2013 Issue: Volume:2013 Page:1-6
ISSN:1085-3375
Container-title:Abstract and Applied Analysis
language:en
Short-container-title:Abstract and Applied Analysis

Author:

Sánchez Antonio Bernardo¹^ORCID,Ordóñez Celestino²^ORCID,Lasheras Fernando Sánchez¹,de Cos Juez Francisco Javier²^ORCID,Roca-Pardiñas Javier³

Affiliation:

1. Departamento de Construcción e Ingeniería de Fabricación, Universidad de Oviedo, 33203 Gijón, Spain

2. Departamento de Explotación y Prospección de Minas, Universidad de Oviedo, Oviedo, 33004 Asturias, Spain

3. Departamento de Estadística, Universidad de Vigo, 36310 Vigo, Spain

Publisher

Hindawi Limited

Subject

Applied Mathematics,Analysis

Link

http://downloads.hindawi.com/journals/aaa/2013/238259.pdf

Reference19 articles.

1. Statistical models and time series forecasting of sulfur dioxide: a case study Tehran

2. Statistical models for the prediction of respirable suspended particulate matter in urban cities

3. Short-term prediction of SO2 concentration in Macau with artificial neural networks

4. The application of neural techniques to the modelling of time-series of atmospheric pollution data

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