Modeling the Context of the Problem Domain of Time Series with Type-2 Fuzzy Sets

Autor:	Anton Romanov, Gleb Guskov, Aleksey Filippov, Valeria V. Voronina, Nadezhda Yarushkina
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Scheme (programming language) Series (mathematics) enterprise planning Computer science tendencies General Mathematics Fuzzy set Context (language use) Predictive analytics computer.software_genre Fuzzy logic context predictive analytics type-2 fuzzy sets Problem domain QA1-939 Computer Science (miscellaneous) Data mining Time series time series Engineering (miscellaneous) computer Mathematics computer.programming_language
Zdroj:	Mathematics Volume 9 Issue 22 Mathematics, Vol 9, Iss 2947, p 2947 (2021)
ISSN:	2227-7390
DOI:	10.3390/math9222947
Popis:	Data analysis in the context of the features of the problem domain and the dynamics of processes are significant in various industries. Uncertainty modeling based on fuzzy logic allows building approximators for solving a large class of problems. In some cases, type-2 fuzzy sets in the model are used. The article describes constructing fuzzy time series models of the analyzed processes within the context of the problem domain. An algorithm for fuzzy modeling of the time series was developed. A new time series forecasting scheme is proposed. An illustrative example of the time series modeling is presented. The benefits of contextual modeling are demonstrated.
Databáze:	OpenAIRE
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