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Volume 2, Issue 1 (2022) –

Cover Picture: The paper proposed a hybrid method for time series summarization. The current work is divided into two parts: The first part is dedicated for extracting the linguistic summaries of the dynamic characteristics of the trends of time series. It is achieved using the traditional genetic algorithm where the fitness function represents the truth degree of the linguistic quantified proposition. The second part is devoted to formalizing the problem of interest as a multi-criteria optimization problem. Finally, the proposed approach overcomes the problem of the overabundance of irrelevant linguistic summaries of the time series. It allows selecting a set of best summaries regarding some relevant criteria.
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