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- W1567662008 abstract "The purpose of this paper is to propose a new, human consistent way to capture the very essence of a dynamic behavior of some sequences of numerical data. Instead of using traditional, notably statistical type analyses, we propose the use of fuzzy logic based linguistic summaries of data(bases) in the sense of Yager, later developed by Kacprzyk and Yager, and Kacprzyk, Yager and Zadrozny. Our main interest is in the summarization of trends characterized by: dynamics of change, duration and variability. To define the dynamic of change of the time series we propose to use for a preprocessing of data a SOM (self-organizing maps) learned with a LVQ (Learning Vector Quantization) algorithm, and then our approach for linguistic summaries of trends." @default.
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- W1567662008 date "2006-01-01" @default.
- W1567662008 modified "2023-10-16" @default.
- W1567662008 title "A Linguistic Approach to a Human-Consistent Summarization of Time Series Using a SOM Learned with a LVQ-Type Algorithm" @default.
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- W1567662008 doi "https://doi.org/10.1007/11840930_18" @default.
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