Estimation of PM10 concentration from air quality data in the vicinity of a major steelworks site in the metropolitan area of Avilés (Northern Spain) using machine learning techniques-Reference-Cited by-同舟云学术

Estimation of PM10 concentration from air quality data in the vicinity of a major steelworks site in the metropolitan area of Avilés (Northern Spain) using machine learning techniques

Published:2018-06-01 Issue:11 Volume:32 Page:3287-3298
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

García Nieto P. J.^ORCID,Sánchez Lasheras F.,García-Gonzalo E.,de Cos Juez F. J.

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

http://link.springer.com/article/10.1007/s00477-018-1565-6/fulltext.html

Reference47 articles.

1. Aurangojeb M (2011) Relationship between PM10, NO2 and particle number concentration: validity of air quality controls. Proc Environ Sci 6:60–69

2. Berk RA (2008) Statistical learning from a regression perspective. Springer, New York

3. Bishop CM (1995) Neural networks for pattern recognition. Oxford University Press, New York

4. Caicoya M, Mirón JA (2003) Lung cancer and smoking in Asturias, Spain. A case-control study. Gac Sanit 17(3):226–230

5. Casteleiro-Roca JL, Quintián H, Calvo-Rolle JL, Corchado E, Meizoso-López MC, Piñón-Pazos A (2016) An intelligent fault detection system for a heat pump installation based on a geothermal heat exchanger. J Appl Log 17:36–47

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