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Air pollution is the presence of dangerous compounds in the air that have a negative impact on health, resulting in millions of premature deaths every year. The high concentration of particulate matter is a significant problem. Understanding the causes of air pollution is therefore critical for avoiding and managing it. This article provides a full assessment as well as a comparative analysis of several Machine Learning models for forecasting air pollution particle matter. Furthermore, the study intends to examine major work in forecasting air quality using ML models. Furthermore, Support Vector Regression was used to analyze the link between training data and projected outcomes for continuous variables.

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Predictive Analysis of Air Quality Index (AQI) and Identification of Influential Factors Using Machine Learning Models

  • 会议论文

  • 发表日期：

    2025年

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  • Safina Shokeen,
  • Taranveer Singh,
  • Shashank Nautiyal,
  • Gautam Sethi

摘要

Air pollution is the presence of dangerous compounds in the air that have a negative impact on health, resulting in millions of premature deaths every year. The high concentration of particulate matter is a significant problem. Understanding the causes of air pollution is therefore critical for avoiding and managing it. This article provides a full assessment as well as a comparative analysis of several Machine Learning models for forecasting air pollution particle matter. Furthermore, the study intends to examine major work in forecasting air quality using ML models. Furthermore, Support Vector Regression was used to analyze the link between training data and projected outcomes for continuous variables.