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In this paper, the performances of different forecasting systems are compared using the daily maximum ozone levels across three locations in Kuwait. The two analytical tools used in this study to forecast daily maximum ozone levels are time series modeling and fuzzy modeling. The structure of the two proposed forecasting models are derived from basic principles, which include a combination of persistence and daily maximum air temperature as input variables.

The two proposed forecasting models /showed significant improvement compared to the pure persistence forecast, which is the model currently used to forecast ambient air pollution in Kuwait. The performance of the two models suggests that daily maximum temperature explains a large proportion of the variation in ozone daily maximum levels …