Adaptive System For Prediction of Air Quality Index

Abstract

Air quality index forecasting is done with machine learning approaches to predict the Air Quality Index. Machine learning is one of the highly appreciated techniques which is able to train a model on big data efficiently with the help of large-scale algorithms on optimization. However, the relationships between both, concentration of Air pollutant particles present and meteorological factors are terribly understood. To make these connections clearer, this project attempted to apply some of the machine learning techniques to predict the Air quality index category based on the data set composed of the daily meteorological data.In thiswe compared four simple algorithms of machine learning, Random forest, KNN (k-nearest neighbors), SVM (support vector machine) and decision tree to find best algorithm for the project.

 Keywords: Data Mining algorithms, Machine Learning algorithms, Meteorological data.