Abstract
Dynamics, or variability over time, is crucial in virtually all real world processes. Among many formal approaches to the description of dynamic behavior is the use of time series, notably those composed of a sequence of real numbers that represent how values of a quantity, variable, etc. evolve over time. Time series are then used for many diverse purposes exemplified by decision making, prediction, etc. However, in all these situations first we have to grasp the very meaning of a particular time series in the sense of what is going on with the quantity or variable whose values it represents.
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Kacprzyk, J., Wilbik, A., Zadrożny, S. (2006). A Linguistic Quantifier Based Aggregation for a Human Consistent Summarization of Time Series. In: Lawry, J., et al. Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34777-1_23
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DOI: https://doi.org/10.1007/3-540-34777-1_23
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