tsam is a python package which uses different machine learning algorithms for the aggregation of typical periods. It is applicable for all type of time series, either weather data, price data, behavioral data, electrical load data or all together. The module is able to significantly reduce input time series for mathmatical models, and therefore the model's complexity and computational time.
To use tsam, first install tsam<installation> and then start aggregating time series <start>.
tsam is open-source available on GitHub and open for collaboration, help requests etc. In case you use tsam in a scientific publication, we kindly request you to cite one of our publications listed in the Further Reading Section <further_reading>.
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