60 search results - page 3 / 12 » Nonlinear Time-Series Prediction with Missing and Noisy Data |
IJON
2007
13 years 5 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...
ICONIP
2004
13 years 7 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 ...
AMC
2006
13 years 5 months ago
2006
The problem of distinguishing density-independent (DI) from density-dependent (DD) demographic time series is important for understanding the mechanisms that regulate populations ...
IJCNN
2007
IEEE
13 years 12 months ago
2007
IEEE
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
IDEAL
2004
Springer
13 years 11 months ago
2004
Springer
Many time series exhibit dynamics over vastly different time scales. The standard way to capture this behavior is to assume that the slow dynamics are a “trend”, to de-trend t...