Forecasting ground-level ozone concentration levels using machine learning

•Meteorological measurements and source factors are considered for the ground-level ozone concentration level prediction.•Ten years of historical data are collected and analyzed.•Frequent pattern data mining algorithms are utilized to reveal the relationship between each parameter.•A long-term high-resolution machine learning ground-level ozone forecasting model is built with high accuracy.