IJON
2007
14 years 10 days ago
2007
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...
IJON
2007
14 years 10 days ago
2007
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...
PRL
2008
14 years 11 days ago
2008
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...
NN
2006
Springer
14 years 11 days ago
2006
Springer
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...
NC
2006
14 years 11 days ago
2006
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
MOR
2006
14 years 11 days ago
2006
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...
KES
2006
Springer
14 years 11 days ago
2006
Springer
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...
JUCS
2006
14 years 11 days ago
2006
: 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...
DKE
2007
14 years 11 days ago
2007
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...
DATAMINE
2007
14 years 11 days ago
2007
Many high level representations of time series have been proposed for data mining, including Fourier transforms, wavelets, eigenwaves, piecewise polynomial models etc. Many researc...