Using a genetic algorithm to derive a linguistic summary of trends in numerical time series

J. Kacprzyk; A. Wilbik; S. Zadrozny

doi:10.1109/ISEFS.2006.251150

Using a genetic algorithm to derive a linguistic summary of trends in numerical time series

J. Kacprzyk^*
, A. Wilbik
, S. Zadrozny

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

The purpose of this paper is to propose a new easily implementable approach to a linguistic summarization of trends that may occur in temporal data, to be more specific - time series. To characterize the trends in time series, we use three parameters: dynamics of change, duration and variability, and apply to them the fuzzy linguistic summaries of data (databases) in the sense of Yager (cf. Yager [13], Kacprzyk and Yager [7] and Kacprzyk, Yager and Zadrozny [8]) which in the form of natural language-like sentences subsume the very essence of a set of data. A genetic algorithm is used to generate the linguistic summaries sought.

Original language	English
Title of host publication	Proceedings of 2006 International Symposium on Evolving Fuzzy Systems
Editors	P. Angelov, D. Filev, N. Kasabov, O. Cordon
Publisher	IEEE Press
Pages	137-142
Number of pages	6
DOIs	https://doi.org/10.1109/ISEFS.2006.251150
Publication status	Published - 2006
Externally published	Yes
Event	3rd International IEEE Conference Intelligent Systems - London, United Kingdom Duration: 4 Sept 2006 → 6 Sept 2006

Conference

Conference	3rd International IEEE Conference Intelligent Systems
Country/Territory	United Kingdom
City	London
Period	4/09/06 → 6/09/06

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10.1109/ISEFS.2006.251150

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title = "Using a genetic algorithm to derive a linguistic summary of trends in numerical time series",

abstract = "The purpose of this paper is to propose a new easily implementable approach to a linguistic summarization of trends that may occur in temporal data, to be more specific - time series. To characterize the trends in time series, we use three parameters: dynamics of change, duration and variability, and apply to them the fuzzy linguistic summaries of data (databases) in the sense of Yager (cf. Yager [13], Kacprzyk and Yager [7] and Kacprzyk, Yager and Zadrozny [8]) which in the form of natural language-like sentences subsume the very essence of a set of data. A genetic algorithm is used to generate the linguistic summaries sought.",

author = "J. Kacprzyk and A. Wilbik and S. Zadrozny",

year = "2006",

doi = "10.1109/ISEFS.2006.251150",

language = "English",

pages = "137--142",

editor = "P. Angelov and D. Filev and N. Kasabov and O. Cordon",

booktitle = "Proceedings of 2006 International Symposium on Evolving Fuzzy Systems",

publisher = "IEEE Press",

address = "United States",

note = "3rd International IEEE Conference Intelligent Systems ; Conference date: 04-09-2006 Through 06-09-2006",

}

Kacprzyk, J, Wilbik, A & Zadrozny, S 2006, Using a genetic algorithm to derive a linguistic summary of trends in numerical time series. in P Angelov, D Filev, N Kasabov & O Cordon (eds), Proceedings of 2006 International Symposium on Evolving Fuzzy Systems. IEEE Press, pp. 137-142, 3rd International IEEE Conference Intelligent Systems, London, United Kingdom, 4/09/06. https://doi.org/10.1109/ISEFS.2006.251150

Using a genetic algorithm to derive a linguistic summary of trends in numerical time series. / Kacprzyk, J.; Wilbik, A.; Zadrozny, S.
Proceedings of 2006 International Symposium on Evolving Fuzzy Systems. ed. / P. Angelov; D. Filev; N. Kasabov; O. Cordon. IEEE Press, 2006. p. 137-142.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

TY - GEN

T1 - Using a genetic algorithm to derive a linguistic summary of trends in numerical time series

AU - Kacprzyk, J.

AU - Wilbik, A.

AU - Zadrozny, S.

PY - 2006

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N2 - The purpose of this paper is to propose a new easily implementable approach to a linguistic summarization of trends that may occur in temporal data, to be more specific - time series. To characterize the trends in time series, we use three parameters: dynamics of change, duration and variability, and apply to them the fuzzy linguistic summaries of data (databases) in the sense of Yager (cf. Yager [13], Kacprzyk and Yager [7] and Kacprzyk, Yager and Zadrozny [8]) which in the form of natural language-like sentences subsume the very essence of a set of data. A genetic algorithm is used to generate the linguistic summaries sought.

AB - The purpose of this paper is to propose a new easily implementable approach to a linguistic summarization of trends that may occur in temporal data, to be more specific - time series. To characterize the trends in time series, we use three parameters: dynamics of change, duration and variability, and apply to them the fuzzy linguistic summaries of data (databases) in the sense of Yager (cf. Yager [13], Kacprzyk and Yager [7] and Kacprzyk, Yager and Zadrozny [8]) which in the form of natural language-like sentences subsume the very essence of a set of data. A genetic algorithm is used to generate the linguistic summaries sought.

U2 - 10.1109/ISEFS.2006.251150

DO - 10.1109/ISEFS.2006.251150

M3 - Conference article in proceeding

SP - 137

EP - 142

BT - Proceedings of 2006 International Symposium on Evolving Fuzzy Systems

A2 - Angelov, P.

A2 - Filev, D.

A2 - Kasabov, N.

A2 - Cordon, O.

PB - IEEE Press

T2 - 3rd International IEEE Conference Intelligent Systems

Y2 - 4 September 2006 through 6 September 2006

ER -

Using a genetic algorithm to derive a linguistic summary of trends in numerical time series

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