E ISSN: 2583-049X

International Journal of Advanced Multidisciplinary Research and Studies

Volume 4, Issue 2, 2024

Air Quality Index Prediction in Punjab using Genetic Algorithm and Artificial Intelligence

Author(s): Dr. Rachhpal Singh, Dr. Parvinder Kaur, Amandeep Kaur


Stubble burning is today’s big problem in Punjab and its surrounding areas. This happens due to the huge quantity of stubble generated after harvesting crops. The requirement of the next crop sowing within a period creates the stubble burning problem that harms our ecosystem and ecology. Stubble burning increases the PM (Particulate Matter) which disturbs our AQI (Air Quality Index) in the environment. To control this, we can make some predictions using AI (Artificial Intelligence) techniques like ML (Machine Learning), DL (Deep Learning) etc. Many conventional algorithms were used for the prediction of AQI like SVM (Support Vector Machine), RF (Random Forest), ANN (Artificial Neural Network), and regression/classification. A hybrid approach of GA (Genetic Algorithm) with RF (Random Forest) as the proposed technique gave better prediction than traditional techniques. In the past five years, air pollution data analyzed from different cities in Punjab has helped estimate and forecast PM levels by using our proposed hybrid RG technique and a comparison with other conventional techniques.

Keywords: Artificial Intelligence, Machine Learning, Air Quality Index, PM2.5, PM10, Support Vector Machine, Artificial Neural Network, Random Forests Correlation and Regression Analysis

Pages: 309-317

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