Time series pattern recognition based on MAP transform and local trend associations

Ildar Batyrshin, Leonid Sheremetov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

The methods of pattern recognition in time series based on moving approximation (MAP) transform and MAP image of patterns are proposed. We discuss main properties of MAP transform, introduce a concept of a MAP image of time series and distance between time series patterns based on this concept which were used for recognition of small patterns in noisy time series. To illustrate the application of this technique to recognition of perception based patterns given by sequence of slopes, an example of recognition of water production patterns in petroleum wells used in expert system for diagnosis of water production problems is considered.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 11th Iberoamerican Congress in Pattern Recognition, CIARP 2006, Proceedings
PublisherSpringer Verlag
Pages910-919
Number of pages10
ISBN (Print)3540465561, 9783540465560
DOIs
StatePublished - 2006
Externally publishedYes
Event11th Iberoamerican Congress in Pattern Recognition, CIARP 2006 - Cancun, Mexico
Duration: 14 Nov 200617 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4225 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Iberoamerican Congress in Pattern Recognition, CIARP 2006
Country/TerritoryMexico
CityCancun
Period14/11/0617/11/06

Keywords

  • Local trend association
  • Moving approximation transform
  • Pattern recognition
  • Time series

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