SENSITIVITY ANALYSIS OF THE EFFECTIVE INPUT PARAMETERS UPON THE OZONE CONCENTRATION USING ARTIFICIAL NEURAL NETWORKS

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GHORBANI MOHAMMAD ALI; NAGHIPOUR LEILA; KARIMI VAHID; FARHOUDI REZA

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Journal: IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT Year:2013 | Volume:6 | Issue:1 Page(s): 11-22

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Title

SENSITIVITY ANALYSIS OF THE EFFECTIVE INPUT PARAMETERS UPON THE OZONE CONCENTRATION USING ARTIFICIAL NEURAL NETWORKS

Author(s)

GHORBANI MOHAMMAD ALI | NAGHIPOUR LEILA | KARIMI VAHID | FARHOUDI REZA | Issue Writer Certificate

Keywords

AIR POLLUTIONQ1

ARTIFICIAL NEURAL NETWORKSQ2

SENSITIVITY ANALYSISQ2

OZONE CONCENTRATIONQ2

TABRIZQ2

Abstract

Background and Objectives: Weather pollution, caused by Ozone (O3) in metropolitans, is one of the major components of pollutants, which damage the environment and hurt all living organisms.Therefore, this study attempts to provide a model for the estimation of O3 concentration in TABRIZ at two pollution monitoring stations: Abresan and Rastekuche.Materials and Methods: In this research, ARTIFICIAL NEURAL NETWORKS (ANNs) were used to consider the impact of the meteorological and weather pollution parameters upon O3 concentration, and weight matrix of ANNs with Garson equation were used for SENSITIVITY ANALYSIS of the input parameters to ANNs.Results: The results indicate that the O3 concentration is simultaneously affected by the meteorological and the weather pollution parameters. Among the meteorological parameters used by ANNs, maximum temperature and among the AIR POLLUTION parameters, carbon monoxide had the maximum effect.Conclusion: The results are representative of the acceptable performance of ANNs to predict O3 concentration. In addition, the parameters used in the modeling process could assess variations of the OZONE CONCENTRATION at the investigated stations.

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APA: Copy

GHORBANI, MOHAMMAD ALI, NAGHIPOUR, LEILA, KARIMI, VAHID, & FARHOUDI, REZA. (2013). SENSITIVITY ANALYSIS OF THE EFFECTIVE INPUT PARAMETERS UPON THE OZONE CONCENTRATION USING ARTIFICIAL NEURAL NETWORKS. IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT, 6(1), 11-22. SID. https://sid.ir/paper/145836/en

Vancouver: Copy

GHORBANI MOHAMMAD ALI, NAGHIPOUR LEILA, KARIMI VAHID, FARHOUDI REZA. SENSITIVITY ANALYSIS OF THE EFFECTIVE INPUT PARAMETERS UPON THE OZONE CONCENTRATION USING ARTIFICIAL NEURAL NETWORKS. IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT[Internet]. 2013;6(1):11-22. Available from: https://sid.ir/paper/145836/en

IEEE: Copy

MOHAMMAD ALI GHORBANI, LEILA NAGHIPOUR, VAHID KARIMI, and REZA FARHOUDI, “SENSITIVITY ANALYSIS OF THE EFFECTIVE INPUT PARAMETERS UPON THE OZONE CONCENTRATION USING ARTIFICIAL NEURAL NETWORKS,” IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT, vol. 6, no. 1, pp. 11–22, 2013, [Online]. Available: https://sid.ir/paper/145836/en

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