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ESANN
2006
13 years 8 months ago
EM-algorithm for training of state-space models with application to time series prediction
In this paper, an improvement to the E step of the EM algorithm for nonlinear state-space models is presented. We also propose strategies for model structure selection when the EM-...
Elia Liitiäinen, Nima Reyhani, Amaury Lendass...
TIT
2011
140views more  TIT 2011»
13 years 2 months ago
Sequential Quantile Prediction of Time Series
Motivated by a broad range of potential applications, we address the quantile prediction problem of real-valued time series. We present a sequential quantile forecasting model bas...
Gérard Biau, Benoît Patra
MICAI
2004
Springer
14 years 25 days ago
Extracting Temporal Patterns from Time Series Data Bases for Prediction of Electrical Demand
In this paper we present a technique for prediction of electrical demand based on multiple models. The multiple models are composed by several local models, each one describing a r...
J. Jesus Rico Melgoza, Juan J. Flores, Constantino...
MIAR
2006
IEEE
14 years 1 months ago
Pulsative Flow Segmentation in MRA Image Series by AR Modeling and EM Algorithm
Segmentation of CSF and pulsative blood flow, based on a single phase contrast MRA (PC-MRA) image can lead to imperfect classifications. In this paper, we present a novel automated...
Ali Gooya, Hongen Liao, Kiyoshi Matsumiya, Ken Mas...
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 2 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