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ENVSOFT
2008
115views more  ENVSOFT 2008»
13 years 5 months ago
Adaptive fuzzy modeling versus artificial neural networks
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
Ralf Wieland, Wilfried Mirschel
ESANN
2008
13 years 7 months ago
Selection of important input variables for RBF network using partial derivatives
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
Jarkko Tikka, Jaakko Hollmén
NPL
2000
138views more  NPL 2000»
13 years 5 months ago
Neural Net Based Hybrid Modeling of the Methanol Synthesis Process
A Hybrid modeling approach, combining an analytical model with a radial basis function neural network is introduced in this paper. The modeling procedure is combined with genetic a...
Primoz Potocnik, Igor Grabec, Marko Setinc, Janez ...
ESANN
2006
13 years 7 months ago
LS-SVM functional network for time series prediction
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...
Tuomas Kärnä, Fabrice Rossi, Amaury Lend...
IJON
2011
90views more  IJON 2011»
12 years 9 months ago
Fault tolerant machine learning for nanoscale cognitive radio
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo