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09 May 2023, Volume 38 Issue 3
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Abstract
Nowadays, advances in improved climate change data analysis and predictions will result in significantly enhanced national economic opportunities, particularly in the agriculture and energy sectors, as well as different social benefits. Data mining algorithm and machine learning algorithms are the best way to analyze and predict various unsolved problems, particularly in climate change-related issues using data mining and machine learning algorithms like data preprocessing, classification, and decision tree approaches. This paper considers different parameters, namely PM2.5, PM10, NO, NO2, NOx, NH3, CO, SO2, O3, Benzene, Toluene, Xylene and AQI. This paper introduces the most critical analysis and prediction results are finding an optimum and suitable model for predicting climate change through AQI using data mining and machine learning with different accuracy parameters. Numerical illustrations were also provided to prove the proposed research.
Keyword
Climate Change, Air Quality Index, Data Mining, Machine Learning, Accuracy Methods.
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