16 search results - page 2 / 4 » Forecasting daily time series using periodic unobserved comp... |
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
WSC
2004
13 years 6 months ago
2004
Forecasting is of prime importance for accuracy in decision making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor ...
MLDM
2009
Springer
13 years 11 months ago
2009
Springer
The paper describes a method for predicting climate time series that consist of significant annual and diurnal seasonal components and a short-term stockastic component. A memory...
TSMC
2008
13 years 4 months ago
2008
Abstract-- In this paper, we address the issue of forecasting for periodically measured nonstationary traffic based on statistical time series modeling. Often with time series base...
IJCSA
2006
13 years 4 months ago
2006
Artificial Neural Networks are universal and highly flexible function approximators first used in the fields of cognitive science and engineering. In recent years, Neural Networks...