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Title

Forecasting air pollutant concentrations using gene expression programming and multiple linear regression in Tehran, Iran

Year: 1394
COI: ATTITTDE01_130
Language: EnglishView: 322
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Authors

Saeed Samadianfard - Assistant Professor, Water Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
Reza Delirhasannia - Assistant Professor, Water Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

Abstract:

The forecasting of air pollutant trends has received much attention in recent years. It is animportant and popular topic in environmental science, as concerns have been raised about thehealth impacts caused by unacceptable ambient air pollutant levels. Of greatest concern aremetropolitan cities like Tehran, Iran. The aim of the present work is to evaluate the potentialof gene expression programming (GEP) in comparison with multiple linear regression (MLR)methods to provide reliable predictions of PM10 and O3 hourly concentrations, a task that isknown to present certain difficulties. The modeling study involves five measurementlocations within the Greater Tehran Area named Azadi, Golhak, Hesar, Pardisan and Vilastations which face significant air pollution problems. The PM10 and O3 data used cover theyear of 2005. The results of MLR were rather satisfactory, with values of the correlationcoefficient (R) for independent test sets ranged between 0.868 and 0.927 for PM10 andbetween 0.756 and 0.927 for O3 for the five stations and values of the index of agreementbetween 0.877 and 0.927 for PM10 and between 0.751 and 0.939 for O3. The performance ofexamined MLR was superior in comparison with GEP models that were developed in parallel(R for GEP models ranged between 0.846 and 0.923 for PM10 and between 0.773 and 0.940for O3). The results of the study clearly demonstrate the proficiency of the multiple linearregression in comparison with gene expression programming in estimating air pollutantconcentrations.

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Paper COI Code

This Paper COI Code is ATTITTDE01_130. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/456440/

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Samadianfard, Saeed and Delirhasannia, Reza,1394,Forecasting air pollutant concentrations using gene expression programming and multiple linear regression in Tehran, Iran,First International Congress on Earth, Space and Clean Energy,Ardabil,https://civilica.com/doc/456440

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  • Corani, G. (2005). Air quality prediction in Milan: Feed-forward neural ...
  • Ferreira, C. (2001a). Gene expression programming in problem solving. 6th ...
  • Ferreira, C. (2001b). Gene expression programming, A new adaptive algorithm ...
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  • Fuchs, M. (1998). Crossover versus mutation: An empirical and theoretical ...
  • Guven, A. and Aytek, A. (2009). New approach for stageedi ...
  • Koza, J.R. (1992). Genetic programming, _ the programming of computers ...
  • Li-Shun Lu. (2006). Air Pollution in Asia, Interactive Qualifying Project, ...
  • Liu, W.C. and Chen, W.B. (2012). Prediction of water temperature ...
  • Logan J. A. (1985). Tropospheric Ozone: Seasonal Behavior, Trends and ...
  • Luke, S. and Spector, L. (1998). A revised comparison of ...
  • Samadianfard, S., Delirhasannia, R., Kisi, O. and Agirre-B asurko, E. ...
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