MODELING VEHICLE AIR POLLUTION ATTRIBUTES BY ARTIFICIAL NEURAL NETWORK

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VAZIRI M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Scientia Iranica Year:2001 | Volume:8 | Issue:1 (CIVIL ENGINEERING) Page(s): 10-15

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Information Journal Paper

Title

MODELING VEHICLE AIR POLLUTION ATTRIBUTES BY ARTIFICIAL NEURAL NETWORK

Author(s)

VAZIRI M. | Issue Writer Certificate

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Abstract

The municipalities of large Iranian cities require regular air pollutant emission monitoring for motor vehicles. The record d data include information about commonly regulated air pollutants and motor vehicle characteristics which were randomly selected and studied from the Tehran database. Regression analysis was found ineffective in modeling the relationships among air pollutant, meteorological and motor vehicle characteristics. However, the artificial neural network, ANN modeling’s seemed to be a useful tool for prediction of air pollutants. The developed ANN models were found 0 be superior to the developed regression models. Application of the study approach and results could improve motor vehicle air quality monitoring and control activities for urban areas.

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APA: Copy

VAZIRI, M.. (2001). MODELING VEHICLE AIR POLLUTION ATTRIBUTES BY ARTIFICIAL NEURAL NETWORK. SCIENTIA IRANICA, 8(1 (CIVIL ENGINEERING)), 10-15. SID. https://sid.ir/paper/289696/en

Vancouver: Copy

VAZIRI M.. MODELING VEHICLE AIR POLLUTION ATTRIBUTES BY ARTIFICIAL NEURAL NETWORK. SCIENTIA IRANICA[Internet]. 2001;8(1 (CIVIL ENGINEERING)):10-15. Available from: https://sid.ir/paper/289696/en

IEEE: Copy

M. VAZIRI, “MODELING VEHICLE AIR POLLUTION ATTRIBUTES BY ARTIFICIAL NEURAL NETWORK,” SCIENTIA IRANICA, vol. 8, no. 1 (CIVIL ENGINEERING), pp. 10–15, 2001, [Online]. Available: https://sid.ir/paper/289696/en

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