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IWANN
1999
Springer
13 years 11 months ago
Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection
A crucial problem in non-linear time series forecasting is to determine its auto-regressive order, in particular when the prediction method is non-linear. We show in this paper tha...
Michel Verleysen, Eric de Bodt, Amaury Lendasse
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 1 months ago
Neural network ensembles for time series forecasting
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
Victor M. Landassuri-Moreno, John A. Bullinaria
JMLR
2011
187views more  JMLR 2011»
13 years 2 months ago
Robust Statistics for Describing Causality in Multivariate Time Series
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Florin Popescu
EDBT
2004
ACM
110views Database» more  EDBT 2004»
14 years 7 months ago
Using Convolution to Mine Obscure Periodic Patterns in One Pass
The mining of periodic patterns in time series databases is an interesting data mining problem that can be envisioned as a tool for forecasting and predicting the future behavior o...
Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagar...
INFOCOM
2009
IEEE
14 years 2 months ago
Measuring Complexity and Predictability in Networks with Multiscale Entropy Analysis
—We propose to use multiscale entropy analysis in characterisation of network traffic and spectrum usage. We show that with such analysis one can quantify complexity and predict...
Janne Riihijärvi, Matthias Wellens, Petri M&a...