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On the use of evolutionary time series analysis for segmenting paleoclimate data

Perez-Ortiz, M. and Duran-Rosal, A. and Gutierrez, P.A. and Sanchez-Monedero, J. and Nikolaou, A. and Fernandez-Navarro, F. and Hervas-Martinez, C. (2014) On the use of evolutionary time series analysis for segmenting paleoclimate data. In: Hybrid Artificial Intelligence Systems, HAIS 2014 (8480), pp. 318-329. Springer. 9th International Conference, HAIS 2014, 11.-13. Juni 2014, Salamanca, Spanien. DOI: 10.1007/978-3-319-07617-1_29

Full text not available from this repository.

Official URL: http://link.springer.com/chapter/10.1007%2F978-3-319-07617-1_29

Abstract

Recent studies propose that some dynamical systems, such as climate, ecological and financial systems, among others, present critical transition points named to as tipping points (TP). Climate TPs can severely affect millions of lives on Earth so that an active scientific community is working on finding early warning signals. This paper deals with the segmentation of a paleoclimate time series to find segments sharing common patterns with the purpose of finding one or more kinds of segments corresponding to TPs. Due to the limitations of classical statistical methods, we propose the use of a genetic algorithm to automatically segment the series together with a method to perform time series segmentation comparisons. Without a priori information, the method clusters together most of the TPs and avoids false positives, which is a promising result given the challenging nature of the problem.

Item URL in elib:https://elib.dlr.de/101735/
Document Type:Conference or Workshop Item (Speech)
Title:On the use of evolutionary time series analysis for segmenting paleoclimate data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Perez-Ortiz, M.UNSPECIFIEDUNSPECIFIED
Duran-Rosal, A.UNSPECIFIEDUNSPECIFIED
Gutierrez, P.A.UNSPECIFIEDUNSPECIFIED
Sanchez-Monedero, J.UNSPECIFIEDUNSPECIFIED
Nikolaou, A.athanasia.nikolaou (at) dlr.deUNSPECIFIED
Fernandez-Navarro, F.UNSPECIFIEDUNSPECIFIED
Hervas-Martinez, C.UNSPECIFIEDUNSPECIFIED
Date:2014
Journal or Publication Title:Hybrid Artificial Intelligence Systems, HAIS 2014
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:Yes
DOI :10.1007/978-3-319-07617-1_29
Page Range:pp. 318-329
Editors:
EditorsEmail
Polycarpou, M.UNSPECIFIED
de Carvalho, André C. P. L. F.UNSPECIFIED
Pan, J.-S.UNSPECIFIED
Woźniak, M.UNSPECIFIED
Quintian, H.UNSPECIFIED
Corchado, E.UNSPECIFIED
Publisher:Springer
Status:Published
Keywords:Time series segmentation, genetic algorithms, clustering, paleoclimate data, tipping points, abrupt climate change
Event Title:9th International Conference, HAIS 2014
Event Location:Salamanca, Spanien
Event Type:international Conference
Event Dates:11.-13. Juni 2014
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Science and Exploration
DLR - Research area:Raumfahrt
DLR - Program:R EW - Erforschung des Weltraums
DLR - Research theme (Project):R - Vorhaben Exploration des Sonnensystems
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Planetary Research
Institute of Planetary Research > Planetary Physics
Deposited By: Rückriemen, Tina
Deposited On:06 Jan 2016 14:56
Last Modified:09 Feb 2017 19:22

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