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Journal of Artificial Intelligence and Metaheuristics
Volume 1 , Issue 2, PP: 08-16 , 2022 | Cite this article as | XML | Html |PDF

Title

Improving the Regression of Air Quality Using Ensemble of Machine Learning Models

  Hamzah A. Alsayadi 1 * ,   Abdelaziz A. Abdelhamid 2 ,   El-Sayed M. El-Kenawy 3 ,   Abdelhameed Ibrahim 4 ,   Marwa M. Eid 5

1  Computer Science Department, Faculty of Sciences, Ibb University, Yemen
    (hamzah.sayadi@cis.asu.edu.eg)

2  Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, 11566, Egypt
    (abdelaziz@cis.asu.edu.eg)

3  Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt
    (skenawy@ieee.org)

4  Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, 35516, Mansoura Egypt
    (afai79@mans.edu.eg,)

5  Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura, Egypt
    (marwa.3eeed@gmail.com)


Doi   :   https://doi.org/10.54216/JAIM.010201

Received: January 20, 2022 Accepted: May 25, 2022

Abstract :

Air pollution is a particularly important problem in most countries right now because of its terrible effects on

both the environment and human health. Big cities are most impacted because of the country’s quick industrial

and economic development. In this paper, the authors proposed various regression model for the prediction of

air quality including decision tree regressor, MLP regressor, SVR, random forest regressor, and K-Neighbors

regressor. The air quality dataset, in Itally cities, is used for training and evaluation the proposed model. The

results show that there is a decrease in RMSE, MAE, MBE, R, R2, RRMSE, NSE, and WI when compared to

the traditional methods.

Keywords :

Air quality; Ensemble model; Machine learning; Regression model

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Cite this Article as :
Style #
MLA Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, El-Sayed M. El-Kenawy, Abdelhameed Ibrahim, Marwa M. Eid. "Improving the Regression of Air Quality Using Ensemble of Machine Learning Models." Journal of Artificial Intelligence and Metaheuristics, Vol. 1, No. 2, 2022 ,PP. 08-16 (Doi   :  https://doi.org/10.54216/JAIM.010201)
APA Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, El-Sayed M. El-Kenawy, Abdelhameed Ibrahim, Marwa M. Eid. (2022). Improving the Regression of Air Quality Using Ensemble of Machine Learning Models. Journal of Journal of Artificial Intelligence and Metaheuristics, 1 ( 2 ), 08-16 (Doi   :  https://doi.org/10.54216/JAIM.010201)
Chicago Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, El-Sayed M. El-Kenawy, Abdelhameed Ibrahim, Marwa M. Eid. "Improving the Regression of Air Quality Using Ensemble of Machine Learning Models." Journal of Journal of Artificial Intelligence and Metaheuristics, 1 no. 2 (2022): 08-16 (Doi   :  https://doi.org/10.54216/JAIM.010201)
Harvard Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, El-Sayed M. El-Kenawy, Abdelhameed Ibrahim, Marwa M. Eid. (2022). Improving the Regression of Air Quality Using Ensemble of Machine Learning Models. Journal of Journal of Artificial Intelligence and Metaheuristics, 1 ( 2 ), 08-16 (Doi   :  https://doi.org/10.54216/JAIM.010201)
Vancouver Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, El-Sayed M. El-Kenawy, Abdelhameed Ibrahim, Marwa M. Eid. Improving the Regression of Air Quality Using Ensemble of Machine Learning Models. Journal of Journal of Artificial Intelligence and Metaheuristics, (2022); 1 ( 2 ): 08-16 (Doi   :  https://doi.org/10.54216/JAIM.010201)
IEEE Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, El-Sayed M. El-Kenawy, Abdelhameed Ibrahim, Marwa M. Eid, Improving the Regression of Air Quality Using Ensemble of Machine Learning Models, Journal of Journal of Artificial Intelligence and Metaheuristics, Vol. 1 , No. 2 , (2022) : 08-16 (Doi   :  https://doi.org/10.54216/JAIM.010201)