174 search results - page 25 / 35 » Neural network ensembles for time series forecasting |
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Voted
IJCNN
2008
IEEE
15 years 3 months ago
2008
IEEE
— Hybrid intelligent systems (HIS) are very successful in tackling problems comprising of more than one distinct computational subtask. For instance, decision-making problems are...
NN
2008
Springer
14 years 9 months ago
2008
Springer
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
IWANN
2009
Springer
15 years 4 months ago
2009
Springer
We study the dynamics of a simple bistable system driven by multiplicative correlated noise. Such system mimics the dynamics of classical attractor neural networks with an addition...
ESANN
2003
14 years 10 months ago
2003
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
ESANN
2000
14 years 10 months ago
2000
: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...