Determining the most important factors of air pollutants on respiratory patients: a statistical study using the multiple linear regression model based on Genetic Algorithm
DOI:
https://doi.org/10.59992/IJSR.2026.v5n10p11الكلمات المفتاحية:
Multiple Linear Regression، Air Pollutants، Ordinary Least Square Method، Bronchial Asthma، Genetic Algorithmالملخص
Atmospheric air pollutants contain particles and gases that are harmful to human health. These pollutants cause chronic diseases and allergies, including bronchitis and bronchial asthma. Accordingly, the research used one of the traditional estimation methods for the normal multiple linear regression model parameters, represented by the ordinary least squares and genetic algorithm methods, to determine the most important influencing variables (dust falling, lead, carbon monoxide, sulfur dioxide, total suspended particles) on patients with bronchial asthma as a response variable in Baghdad, 2004. It was shown through data analysis that the variable carbon monoxide and total suspended particles do not have any significant effects on the number of people from bronchial asthma.
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