Chemo-inspired genetic algorithm for optimizing the piecewise aggregate approximation

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

In a previous work we presented DEWPAA: an improved version of the piecewise aggregate approximation representation method of time series. DEWPAA uses differential evolution to set weights to different segments of the time series according to their information content. In this paper we use a hybrid of bacterial foraging and genetic algorithm (CGA) to set the weights of the different segments in our improved piecewise aggregate approximation. Our experiments show that the new hybrid gives better results in time series clasification.

Original languageEnglish
Title of host publicationICORES 2015 - 4th International Conference on Operations Research and Enterprise Systems, Proceedings
EditorsBegona Vitoriano, Greg H. Parlier
PublisherSciTePress
Pages205-210
Number of pages6
ISBN (Electronic)9789897580758
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event4th International Conference on Operations Research and Enterprise Systems - Lisbon, Portugal
Duration: 10 Jan 201512 Jan 2015
Conference number: 4th
http://www.icores.org/?y=2015

Publication series

NameICORES 2015 - 4th International Conference on Operations Research and Enterprise Systems, Proceedings

Conference

Conference4th International Conference on Operations Research and Enterprise Systems
Abbreviated titleICORES 2015
CountryPortugal
CityLisbon
Period10/01/1512/01/15
Internet address

Keywords

  • Bacterial Foraging
  • Chemotaxis
  • Genetic Algorithm
  • Hybridization
  • Piecewise Aggregate Approximation
  • Time Series

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Control and Systems Engineering

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