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2018 | OriginalPaper | Buchkapitel

About Transformations of a Numerical Time Series Using a Linguistic Variable

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Abstract

Time series transforming is considered as a preprocessing stage in various data mining techniques. To obtain relevant and accurate result in time series analysis it is needed to apply relevant time series representation by suitable transformation. In the paper at the first time five transformations of a numerical time series derived on the basis of a single linguistic variable of time series values are described systematically. The formal notion of five kinds (fuzzy matrix, fuzzy vectors, fuzzy linguistic, numerical and linguistic) of time series produced by these transformations and general scheme of their computing are represented. Applications of these five representations of a numerical time series in data mining techniques are given and discussed.

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Metadaten
Titel
About Transformations of a Numerical Time Series Using a Linguistic Variable
verfasst von
Tatyana Afanasieva
Yriy Egorov
Nikolay Savinov
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-68321-8_23