Change Point Detection in Piecewise Stationary Time Series for Farm Animal Behavior Analysis

Sandra Breitenberger (), Dmitry Efrosinin, Wolfgang Auer, Andreas Deininger and Ralf Waßmuth
Additional contact information
Sandra Breitenberger: Linz Center of Mechatronics GmbH (LCM)
Dmitry Efrosinin: Johannes Kepler University Linz
Wolfgang Auer: Smartbow GmbH
Andreas Deininger: Urban GmbH & Co. KG
Ralf Waßmuth: Hochschule Osnabrück

A chapter in Operations Research Proceedings 2015, 2017, pp 369-375 from Springer

Abstract: Abstract Detection of abrupt changes in time series data structure is very useful in modeling and prediction in many application areas, where time series pattern recognition must be implemented. Despite of the wide amount of research in this area, the proposed methods require usually a long execution time and do not provide the possibility to estimate the real changes in variance and autocorrelation at certain points. Hence they cannot be efficiently applied to the large time series where only the change points with constraints must be detected. In the framework of the present paper we provide heuristic methods based on the moving variance ratio and moving median difference for identification of change points. The methods were applied for behavior analysis of farm animals using the data sets of accelerations obtained by means of the radio frequency identification (RFID).

Keywords: Change Point; Change Point Detection; Dairy Calf; Change Point Model; Drinking Period (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-42902-1_50

Ordering information: This item can be ordered from
http://www.springer.com/9783319429021

DOI: 10.1007/978-3-319-42902-1_50

Access Statistics for this chapter

More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().