… In order to do this, we use Self Organizing Maps (SOM). Once the companies in clusters …
Multivariate Adaptive Regression Splines (MARS). Our results show that the proposed hybrid …

… Multivariate adaptative regression splines (MARS) is a data mining technique with a well-…
A self-organizing map (SOM) is a type of neural network what was used here to determine a …

… - plate spline (TPS) interpolation to generate a large amount of prediction data for a model
formulation, 9 and we applied the SOM … lipid membrane using a TPS and SOM hybrid method. …

… precision and the hybrid wavelet-ANFIS model performs better than the other models. …
The GMDH algorithm is a learning machine based on self-organizing approach, presented by …

… We propose instead to estimate a separate classification device for each one of the groups
identified in the cluster analysis. Authors such as Hush and Horne, 1993, Gopalakrishnan et …

… swarm optimization–support vector machine hybrid model to first … technique of a self-organizing
map (SOM) is implemented as … and in hybrid designs with EEDM and an SOM to capture …

… That is, although the low-dimensional self-organizing map cannot … in the SOM. Compared
with other statistical nonlinear … device to accomplish the classification task suggested by this …

… is that we develop a hybrid self-learning model for … Self-Organizing Maps (SOM) is adopted
for data kernelization and preparation of further smoothing; (2) Classification and Regression …

… It discusses various recent methods such as self-organizing maps, … Kohonen’s self-organizing
map (SOM) is an abstract, … in mathematical form the selforganising topographic mappings, …

… Self-Organizing Map (SOM) and the traditional DRASTIC model resulting in the hybrid SOM-…
and a method named supervised committee machine artificial intelligent (SCMAI) to obtain …