INTRODUCING AN APPROPRIATE MODEL USING SUPPORT VECTOR MACHINE FOR PREDICTING CARBON MONOXIDE DAILY CONCENTRATION IN TEHRAN ATMOSPHERE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

NOORI ROOHOLLAH; HOSHYARIPOUR GHOLAMALI; ASHRAFI KHOSRO; RASTI OMRAN

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

Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT Year:2013 | Volume:6 | Issue:1 Page(s): 1-10

Download Full-Text

Persian Verion

View:

703

Download:

Cites:

Information Journal Paper

Title

INTRODUCING AN APPROPRIATE MODEL USING SUPPORT VECTOR MACHINE FOR PREDICTING CARBON MONOXIDE DAILY CONCENTRATION IN TEHRAN ATMOSPHERE

Author(s)

NOORI ROOHOLLAH | HOSHYARIPOUR GHOLAMALI | ASHRAFI KHOSRO | RASTI OMRAN | Issue Writer Certificate

Keywords

CARBON MONOXIDEQ2

SUPPORT VECTOR MACHINEQ2

FORWARD SELECTIONQ2

TEHRANQ2

Abstract

Backgrounds and Objectives: Precise air pollutants prediction, as the first step in facing air pollution problem, could provide helpful information for authorities in order to have appropriate actions toward this challenge. Regarding the importance of CARBON MONOXIDE (CO) in TEHRAN atmosphere, this study aims to introduce a suitable model for predicting this pollutant.Materials and Method: We used the air pollutants and meteorological data of Gholhak station located in the north of TEHRAN; these data provided 12 variables as inputs for predicting the average CO concentration of the next day. First, SUPPORT VECTOR MACHINE (SVM) model was used for forecasting CO daily average concentration. Then, we reduced the SVM inputs to seven variables using FORWARD SELECTION (FS) method. Finally, the hybrid model, FS-SVM, was developed for CO daily average concentration forecasting.Result: In the research, we used correlation coefficient to evaluate the accuracy of both SVM and FS-SVM models. Findings indicated that correlation coefficient for both models in testing step was equal (R~0.88). It means that both models have proper accuracy for predicting CO concentration. However, it is noteworthy that FS-SVM model charged fewer amounts of computational and economical costs due to fewer inputs than SVM model.Conclusion: Results showed that although both models have relatively equal accuracy in predicting CO concentration, FS-SVM model is the superior model due to its less number of inputs and therefore, less computational burden.

Cites

No record.

References

No record.

Cite

APA: Copy

NOORI, ROOHOLLAH, HOSHYARIPOUR, GHOLAMALI, ASHRAFI, KHOSRO, & RASTI, OMRAN. (2013). INTRODUCING AN APPROPRIATE MODEL USING SUPPORT VECTOR MACHINE FOR PREDICTING CARBON MONOXIDE DAILY CONCENTRATION IN TEHRAN ATMOSPHERE. IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT, 6(1), 1-10. SID. https://sid.ir/paper/145840/en

Vancouver: Copy

NOORI ROOHOLLAH, HOSHYARIPOUR GHOLAMALI, ASHRAFI KHOSRO, RASTI OMRAN. INTRODUCING AN APPROPRIATE MODEL USING SUPPORT VECTOR MACHINE FOR PREDICTING CARBON MONOXIDE DAILY CONCENTRATION IN TEHRAN ATMOSPHERE. IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT[Internet]. 2013;6(1):1-10. Available from: https://sid.ir/paper/145840/en

IEEE: Copy

ROOHOLLAH NOORI, GHOLAMALI HOSHYARIPOUR, KHOSRO ASHRAFI, and OMRAN RASTI, “INTRODUCING AN APPROPRIATE MODEL USING SUPPORT VECTOR MACHINE FOR PREDICTING CARBON MONOXIDE DAILY CONCENTRATION IN TEHRAN ATMOSPHERE,” IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT, vol. 6, no. 1, pp. 1–10, 2013, [Online]. Available: https://sid.ir/paper/145840/en

Related Journal Papers