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How to cite (IEEE):
M. Hassan, S. Mostafa, Z. Baharum, A. Mustapha, M. Saringat, & R. Afyenni
"A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment," JOIV : International Journal on Informatics Visualization, vol. 6, no. 4, , pp. 876-882, Dec. 2022.
https://doi.org/10.30630/joiv.6.4.1228
How to cite (APA):
Hassan, M., Mostafa, S., Baharum, Z., Mustapha, A., Saringat, M., & Afyenni, R.
(2022).
A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment.
JOIV : International Journal on Informatics Visualization, 6(4), 876-882.
https://doi.org/10.30630/joiv.6.4.1228
How to cite (Chicago):
Hassan, Mustafa Hamid, Mostafa, Salama A., Baharum, Zirawani, Mustapha, Aida, Saringat, Mohd Zainuri, AND Afyenni, Rita.
"A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment" JOIV : International Journal on Informatics Visualization [Online], Volume 6 Number 4 (31 December 2022)
https://doi.org/10.30630/joiv.6.4.1228
How to cite (Vancouver):
Hassan M, Mostafa S, Baharum Z, Mustapha A, Saringat M, & Afyenni R .
A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment.
JOIV : International Journal on Informatics Visualization [Online]. 2022 Dec;
6(4):876-882.
https://doi.org/10.30630/joiv.6.4.1228
How to cite (Harvard):
Hassan, M., Mostafa, S., Baharum, Z., Mustapha, A., Saringat, M., & Afyenni, R.
,2022.
A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment.
JOIV : International Journal on Informatics Visualization, [Online] 6(4), pp. 876-882.
https://doi.org/10.30630/joiv.6.4.1228
How to cite (MLA8):
Hassan, Mustafa Hamid, Salama A. Mostafa, Zirawani Baharum, Aida Mustapha, Mohd Zainuri Saringat, & Rita Afyenni.
"A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment." JOIV : International Journal on Informatics Visualization [Online], 6.4 (2022): 876-882. Web. 3 Oct. 2023
, https://doi.org/10.30630/joiv.6.4.1228
BibTex Citation Data :
@article{JOIV1228,
author = {Mustafa Hamid Hassan and Salama A. Mostafa and Zirawani Baharum and Aida Mustapha and Mohd Zainuri Saringat and Rita Afyenni},
title = {A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment},
journal = {JOIV : International Journal on Informatics Visualization},
volume = {6},
number = {4},
year = {2022},
keywords = {Air pollution; dynamic risk; Monte Carlo simulation; nested Monte Carlo Simulation.},
abstract = {The risk assessment of air pollution is an essential matter in the area of air quality computing. It provides useful information supporting air quality (AQ) measurement and pollution control. The outcomes of the evaluation have societal and technical influences on people and decision-makers. The existing air pollution risk assessment employs different qualitative and quantitative methods. This study aims to develop an AQ-risk model based on the Nested Monte Carlo Simulation (NMCS) and concentrations of several air pollutant parameters for forecasting daily AQ in the atmosphere. The main idea of NMCS lies in two main parts, which are the Outer and Inner parts. The Outer part interacts with the data sources and extracts a proper sampling from vast data. It then generates a scenario based on the data samples. On the other hand, the Inner part handles the assessment of the processed risk from each scenario and estimates future risk. The AQ-risk model is tested and evaluated using real data sources representing crucial pollution. The data is collected from an Italian city over a period of one year. The performance of the proposed model is evaluated based on statistical indices, coefficient of determination (R2), and mean square error (MSE). R2 measures the prediction ability in the testing stage for both parameters, resulting in 0.9462 and 0.9073 prediction accuracy. Meanwhile, MSE produced average results of 9.7 and 10.3, denoting that the AQ-risk model provides a considerably high prediction accuracy.},
issn = {2549-9904}, pages = {876--882}, doi = {10.30630/joiv.6.4.1228},
url = {https://joiv.org/index.php/joiv/article/view/1228}
}
Refworks Citation Data :
@article{{JOIV}{1228}, author = {Hassan, M., Mostafa, S., Baharum, Z., Mustapha, A., Saringat, M., Afyenni, R.}, title = {A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {6}, number = {4}, year = {2022}, doi = {10.30630/joiv.6.4.1228}, url = {} }Refbacks
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JOIV : International Journal on Informatics Visualization
ISSN 2549-9610 (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
W : http://joiv.org
E : joiv@pnp.ac.id, hidra@pnp.ac.id, rahmat@pnp.ac.id
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is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.