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» LS-SVM functional network for time series prediction
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GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
14 years 2 months ago
A new evolutionary method for time series forecasting
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
CIKM
2011
Springer
12 years 8 months ago
Hybrid models for future event prediction
We present a hybrid method to turn off-the-shelf information retrieval (IR) systems into future event predictors. Given a query, a time series model is trained on the publication...
Giuseppe Amodeo, Roi Blanco, Ulf Brefeld
IJON
2002
103views more  IJON 2002»
13 years 8 months ago
RBF networks training using a dual extended Kalman filter
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...
Iulian B. Ciocoiu
NN
2000
Springer
192views Neural Networks» more  NN 2000»
13 years 8 months ago
A new algorithm for learning in piecewise-linear neural networks
Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consistin...
Emad Gad, Amir F. Atiya, Samir I. Shaheen, Ayman E...
EVOW
2009
Springer
14 years 3 months ago
Predicting Turning Points in Financial Markets with Fuzzy-Evolutionary and Neuro-Evolutionary Modeling
Two independent evolutionary modeling methods, based on fuzzy logic and neural networks respectively, are applied to predicting trend reversals in financial time series, and their...
Antonia Azzini, Célia da Costa Pereira, And...