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Ground level ozone is one of the common pollution issues that has a negative influence on human health. The key characteristic behind ozone level analysis lies on the complex representation of such data which can be shown by time series. Clustering is one of the common techniques that have been used for time series metrological and environmental data. The way that clustering technique groups the similar sequences relies on a distance or similarity criteria. Several distance measures have beendoi:10.18517/ijaseit.6.6.1482 fatcat:2stquymwnngkvjnwy7ios4skvm