ML
2000
ACM
13 years 4 months ago
2000
ACM
We consider the problem of one-step ahead prediction for time series generated by an underlying stationary stochastic process obeying the condition of absolute regularity, describi...
CSDA
2004
13 years 4 months ago
2004
In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...
IJON
2007
13 years 4 months 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
13 years 4 months 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...
GECCO
2008
Springer
13 years 5 months ago
2008
Springer
This paper presents an study about a new Hybrid method GRASPES - for time series prediction, inspired in F. Takens theorem and based on a multi-start metaheuristic for combinatori...
ICONIP
2004
13 years 6 months ago
2004
Recently, the Support Vector Regression (SVR) has been applied in the financial time series prediction. The financial data are usually highly noisy and contain outliers. Detecting ...
ESANN
2006
13 years 6 months ago
2006
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-...
ESANN
2006
13 years 6 months ago
2006
Usually time series prediction is done with regularly sampled data. In practice, however, the data available may be irregularly sampled. In this case the conventional prediction me...
ESANN
2008
13 years 6 months ago
2008
This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
IJCNN
2000
IEEE
13 years 9 months ago
2000
IEEE
Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results fro...