# Cite Article

### Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate

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@article{IJASEIT12675, author = {Laith Fadhil S. H and Auday Taha R and Waleed Mohammed Elaibi}, title = {Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate}, journal = {International Journal on Advanced Science, Engineering and Information Technology}, volume = {10}, number = {5}, year = {2020}, pages = {1898--1905}, keywords = {generalized partial linear regression model; parametric model; non-parametric model; link function; dust storms.}, abstract = {The phenomenon of dust that occurs in Iraq is one of the phenomena that cannot be completely controlled or partially processed in a short time. It also works to know how some climatic factors such as the average wind speed, relative humidity, atmospheric pressure above sea level, and the maximum temperature which represent explanatory (independent) variables , respectively. The effects on the number of occurrences of dust storms represent the adopted variable (Y) in Baghdad Governorate for the period from 2008 to mid-2013. The researchers used the Generalized Partial Linear Regression Model (GPLRM) consist of fourteen models, after determining the best link function for each model. Then we compared these models to determine the best model that represents this data with the best representation using the Akaike information criterion (AIC), the Schwartz information criterion (BIC), and the determination Coefficient criterion . We also used the program (i- xplore) in the calculation, and we have concluded that the best model is the model in which the variable relative humidity and the maximum temperature in the parametric part, i.e., linear and stable. On the other hand, the variable average wind speed and the variable atmospheric pressure above sea level are non-parametric and their behavior is non-linear and unstable. The researchers consider that Baghdad Governorate suffers from this negative phenomenon as well as in general in Iraq. Besides, the effect of the variable relative humidity is a decreasingly negative effect, while the effect of the variable maximum temperature, it is an increasingly positive effect.

}, issn = {2088-5334}, publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development}, url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12675}, doi = {10.18517/ijaseit.10.5.12675} }

## EndNote

%A Fadhil S. H, Laith %A Taha R, Auday %A Elaibi, Waleed Mohammed %D 2020 %T Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate %B 2020 %9 generalized partial linear regression model; parametric model; non-parametric model; link function; dust storms. %! Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate %K generalized partial linear regression model; parametric model; non-parametric model; link function; dust storms. %XThe phenomenon of dust that occurs in Iraq is one of the phenomena that cannot be completely controlled or partially processed in a short time. It also works to know how some climatic factors such as the average wind speed, relative humidity, atmospheric pressure above sea level, and the maximum temperature which represent explanatory (independent) variables , respectively. The effects on the number of occurrences of dust storms represent the adopted variable (Y) in Baghdad Governorate for the period from 2008 to mid-2013. The researchers used the Generalized Partial Linear Regression Model (GPLRM) consist of fourteen models, after determining the best link function for each model. Then we compared these models to determine the best model that represents this data with the best representation using the Akaike information criterion (AIC), the Schwartz information criterion (BIC), and the determination Coefficient criterion . We also used the program (i- xplore) in the calculation, and we have concluded that the best model is the model in which the variable relative humidity and the maximum temperature in the parametric part, i.e., linear and stable. On the other hand, the variable average wind speed and the variable atmospheric pressure above sea level are non-parametric and their behavior is non-linear and unstable. The researchers consider that Baghdad Governorate suffers from this negative phenomenon as well as in general in Iraq. Besides, the effect of the variable relative humidity is a decreasingly negative effect, while the effect of the variable maximum temperature, it is an increasingly positive effect.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12675 %R doi:10.18517/ijaseit.10.5.12675 %J International Journal on Advanced Science, Engineering and Information Technology %V 10 %N 5 %@ 2088-5334

## IEEE

Laith Fadhil S. H,Auday Taha R and Waleed Mohammed Elaibi,"Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate,"International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 5, pp. 1898-1905, 2020. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.10.5.12675.

## RefMan/ProCite (RIS)

TY - JOUR AU - Fadhil S. H, Laith AU - Taha R, Auday AU - Elaibi, Waleed Mohammed PY - 2020 TI - Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate JF - International Journal on Advanced Science, Engineering and Information Technology; Vol. 10 (2020) No. 5 Y2 - 2020 SP - 1898 EP - 1905 SN - 2088-5334 PB - INSIGHT - Indonesian Society for Knowledge and Human Development KW - generalized partial linear regression model; parametric model; non-parametric model; link function; dust storms. N2 -The phenomenon of dust that occurs in Iraq is one of the phenomena that cannot be completely controlled or partially processed in a short time. It also works to know how some climatic factors such as the average wind speed, relative humidity, atmospheric pressure above sea level, and the maximum temperature which represent explanatory (independent) variables , respectively. The effects on the number of occurrences of dust storms represent the adopted variable (Y) in Baghdad Governorate for the period from 2008 to mid-2013. The researchers used the Generalized Partial Linear Regression Model (GPLRM) consist of fourteen models, after determining the best link function for each model. Then we compared these models to determine the best model that represents this data with the best representation using the Akaike information criterion (AIC), the Schwartz information criterion (BIC), and the determination Coefficient criterion . We also used the program (i- xplore) in the calculation, and we have concluded that the best model is the model in which the variable relative humidity and the maximum temperature in the parametric part, i.e., linear and stable. On the other hand, the variable average wind speed and the variable atmospheric pressure above sea level are non-parametric and their behavior is non-linear and unstable. The researchers consider that Baghdad Governorate suffers from this negative phenomenon as well as in general in Iraq. Besides, the effect of the variable relative humidity is a decreasingly negative effect, while the effect of the variable maximum temperature, it is an increasingly positive effect.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12675 DO - 10.18517/ijaseit.10.5.12675

## RefWorks

RT Journal Article ID 12675 A1 Fadhil S. H, Laith A1 Taha R, Auday A1 Elaibi, Waleed Mohammed T1 Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate JF International Journal on Advanced Science, Engineering and Information Technology VO 10 IS 5 YR 2020 SP 1898 OP 1905 SN 2088-5334 PB INSIGHT - Indonesian Society for Knowledge and Human Development K1 generalized partial linear regression model; parametric model; non-parametric model; link function; dust storms. AB