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IJON
2007
118views more  IJON 2007»
13 years 4 months ago
CATS benchmark time series prediction by Kalman smoother with cross-validated noise density
This article presents the winning solution to the CATS time series prediction competition. The solution is based on classical optimal linear estimation theory. The proposed method...
Simo Särkkä, Aki Vehtari, Jouko Lampinen
IJON
2007
118views more  IJON 2007»
13 years 4 months ago
Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm
To predict the 100 missing values from a time series of 5000 data points, given for the IJCNN 2004 time series prediction competition, recurrent neural networks (RNNs) are trained...
Xindi Cai, Nian Zhang, Ganesh K. Venayagamoorthy, ...
PRL
2008
65views more  PRL 2008»
13 years 4 months ago
Matching of quasi-periodic time series patterns by exchange of block-sorting signatures
We propose a novel method for quasi-periodic time series patterns matching, through signature exchange between the two patterns. The signature is obtained through sorting of the t...
Bachir Boucheham
NN
2006
Springer
105views Neural Networks» more  NN 2006»
13 years 4 months ago
Unfolding preprocessing for meaningful time series clustering
Clustering methods are commonly applied to time series, either as a preprocessing stage for other methods or in their own right. In this paper it is explained why time series clus...
Geoffroy Simon, John Aldo Lee, Michel Verleysen
NC
2006
132views Neural Networks» more  NC 2006»
13 years 4 months ago
Learning short multivariate time series models through evolutionary and sparse matrix computation
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
Stephen Swift, Joost N. Kok, Xiaohui Liu
MOR
2006
73views more  MOR 2006»
13 years 4 months ago
Permuted Standardized Time Series for Steady-State Simulations
We describe an extension procedure for constructing new standardized time series procedures from existing ones. The approach is based on averaging over sample paths obtained by per...
James M. Calvin, Marvin K. Nakayama
KES
2006
Springer
13 years 4 months ago
Predicting Cluster Formation in Decentralized Sensor Grids
This paper investigates cluster formation in decentralized sensor grids and focusses on predicting when the cluster formation converges to a stable configuration. The traffic volum...
Astrid Zeman, Mikhail Prokopenko
JUCS
2006
138views more  JUCS 2006»
13 years 4 months ago
Analysing Data of Childhood Acute Lymphoid Leukaemia by Seasonal Time Series Methods
: We examined the periodicity of the childhood leukaemia in Hungary using seasonal decomposition time series. Between 1988 and 2000 the number of annually diagnosed leukaemia (inci...
Maria Fazekas
DKE
2007
153views more  DKE 2007»
13 years 4 months ago
Adaptive similarity search in streaming time series with sliding windows
The challenge in a database of evolving time series is to provide efficient algorithms and access methods for query processing, taking into consideration the fact that the databas...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...
DATAMINE
2007
135views more  DATAMINE 2007»
13 years 4 months ago
Experiencing SAX: a novel symbolic representation of time series
Many high level representations of time series have been proposed for data mining, including Fourier transforms, wavelets, eigenwaves, piecewise polynomial models etc. Many researc...
Jessica Lin, Eamonn J. Keogh, Li Wei, Stefano Lona...