An Effective System to Forecast Environmental Pollution using Air Quality Index


Authors : Mohammad Ishaque Ali, K. Yasudha

Volume/Issue : Volume 5 - 2020, Issue 4 - April

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/2KMjjun

Abstract : One of the major issues we are facing all around the world is “GLOBAL WARMING” and its effects on our daily life which is only due to poor Air quality. It is something when the earth’s surface temperature increases slowly and makes the air quality poor. The poor air quality affects human health in many ways. The Machine Learning Algorithm (ML), is used to predict Air quality Index. The main focus of the paper is to establish the relationship between dependent data and independent data. Here, we go through the various feature engineering processes to analyze that which machine learning algorithm must be used that can give the best result and less overfitting.

Keywords : Air Pollution, Particulate matter, Decision Tree Regression, Feature Engineering, Human Freedom Index, Linear Regression, Machine Learning, Mutual Information, Random Forest Regression.

One of the major issues we are facing all around the world is “GLOBAL WARMING” and its effects on our daily life which is only due to poor Air quality. It is something when the earth’s surface temperature increases slowly and makes the air quality poor. The poor air quality affects human health in many ways. The Machine Learning Algorithm (ML), is used to predict Air quality Index. The main focus of the paper is to establish the relationship between dependent data and independent data. Here, we go through the various feature engineering processes to analyze that which machine learning algorithm must be used that can give the best result and less overfitting.

Keywords : Air Pollution, Particulate matter, Decision Tree Regression, Feature Engineering, Human Freedom Index, Linear Regression, Machine Learning, Mutual Information, Random Forest Regression.

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