Brunel University Research Archive (BURA) >
Research Areas >
Information Systems and Computing >

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3274

Title: Learning short multivariate time series models through evolutionary and sparse matrix computation
Authors: Swift, S
Kok, J
Liu, X
Keywords: Glaucoma
Natural computation
Short multivariate time series
Sparse matrices
Short-term
Forecasting
Publication Date: 2005
Citation: Natural Computing. 5(4): 387-426
Abstract: Multivariate time series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is important for many decision making activities. One area that has been largely overlooked so far is the particular type of time series where the data set consists of a large number of variables but with a small number of observations. In this paper we describe the development of a novel computational method based on Natural Computation and sparse matrices that bypasses the size restrictions of traditional statistical MTS methods, makes no distribution assumptions, and also locates the associated parameters. Extensive results are presented, where the proposed method is compared with both traditional statistical and heuristic search techniques and evaluated on a number of criteria. The results have implications for a wide range of applications involving the learning of short MTS models.
URI: http://www.springerlink.com/content/bhp28r446253227k/
http://bura.brunel.ac.uk/handle/2438/3274
DOI: http://dx.doi.org/10.1007/s11047-006-9005-9
ISSN: 1572-9796
Appears in Collections:Information Systems and Computing
School of Information Systems, Computing and Mathematics Research Papers

Files in This Item:

File Description SizeFormat
Learning Short Multivariate Time Series Models through Evolutionary.pdf609.21 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.

 


Library (c) Brunel University.    Powered By: DSpace
Send us your
Feedback. Last Updated: September 14, 2010.
Managed by:
Hassan Bhuiyan