Perception based associations in time series data bases

I. Z. Batyrshin; L. B. Sheremetov

doi:10.1109/NAFIPS.2006.365487

Perception based associations in time series data bases

I. Z. Batyrshin, L. B. Sheremetov

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

4 Scopus citations

Abstract

The paper discusses different aspects of the development of perception-based decision making systems. These systems are based on inference procedures transforming associations extracted from the time series data bases into generalized-constraint inference rules. Different types of simple and composite perception based constraints are discussed. Various measures of association between time series in the presence of perception based constraints are considered: association rules, association rules with perception based frequencies, correlation rules, and local trend associations based on moving approximations. Finally, the methods of transformation of these associations into the inference rules that can be used in perception based reasoning are proposed.

Original language	English
Title of host publication	Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Pages	655-660
Number of pages	6
DOIs	https://doi.org/10.1109/NAFIPS.2006.365487
State	Published - 2006
Externally published	Yes
Event	NAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society - Montreal, QC, Canada Duration: 3 Jun 2006 → 6 Jun 2006

Publication series

Name	Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

Conference	NAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society
Country/Territory	Canada
City	Montreal, QC
Period	3/06/06 → 6/06/06

Access to Document

10.1109/NAFIPS.2006.365487

Cite this

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title = "Perception based associations in time series data bases",

abstract = "The paper discusses different aspects of the development of perception-based decision making systems. These systems are based on inference procedures transforming associations extracted from the time series data bases into generalized-constraint inference rules. Different types of simple and composite perception based constraints are discussed. Various measures of association between time series in the presence of perception based constraints are considered: association rules, association rules with perception based frequencies, correlation rules, and local trend associations based on moving approximations. Finally, the methods of transformation of these associations into the inference rules that can be used in perception based reasoning are proposed.",

author = "Batyrshin, {I. Z.} and Sheremetov, {L. B.}",

year = "2006",

doi = "10.1109/NAFIPS.2006.365487",

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pages = "655--660",

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note = "NAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society ; Conference date: 03-06-2006 Through 06-06-2006",

}

Batyrshin, IZ & Sheremetov, LB 2006, Perception based associations in time series data bases. in Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS., 4216880, Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, pp. 655-660, NAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society, Montreal, QC, Canada, 3/06/06. https://doi.org/10.1109/NAFIPS.2006.365487

Perception based associations in time series data bases. / Batyrshin, I. Z.; Sheremetov, L. B.
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS. 2006. p. 655-660 4216880 (Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS).

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

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N2 - The paper discusses different aspects of the development of perception-based decision making systems. These systems are based on inference procedures transforming associations extracted from the time series data bases into generalized-constraint inference rules. Different types of simple and composite perception based constraints are discussed. Various measures of association between time series in the presence of perception based constraints are considered: association rules, association rules with perception based frequencies, correlation rules, and local trend associations based on moving approximations. Finally, the methods of transformation of these associations into the inference rules that can be used in perception based reasoning are proposed.

AB - The paper discusses different aspects of the development of perception-based decision making systems. These systems are based on inference procedures transforming associations extracted from the time series data bases into generalized-constraint inference rules. Different types of simple and composite perception based constraints are discussed. Various measures of association between time series in the presence of perception based constraints are considered: association rules, association rules with perception based frequencies, correlation rules, and local trend associations based on moving approximations. Finally, the methods of transformation of these associations into the inference rules that can be used in perception based reasoning are proposed.

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Perception based associations in time series data bases

Abstract

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Conference

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