… Self-organizing maps (SOM) are used as a visualization technique for design space exploration
that permits identifying RoI. Conventional implementation of SOM is susceptible to folds …

… This study applied self-organizing map and hierarchical clustering algorithms to … self-organizing
map and hierarchical clustering algorithms in tandem can be a useful exploratory data …

… Abstract: A model integrating geo-information and self-organizing map (SOM) for exploring
… Data exploration process based on the self-organizing map [D]. Helsinki: Helsinki University …

… map for tackling clustering problems and data exploration. Each neuron contains a vector
with the same dimensionality of the input vector. The neurons are subsequently adjusted …

… We propose a novel improved adaptive version of the Self-Organizing Map (SOM). Our
enhancement of SOM adapts to the input data scattering, in this way, preserving the principal …

… , is a necessary process to divide and classify students into classes based on their abilities
and … A self-organizing map (SOM) is an example of unsupervised learning algorithm using an …

… are available for data exploration and they … methods, Self-Organizing Map (SOM) is an
artificial neural network able to handle non-linear problems that can be used for exploratory data …

… the ways to interpret and visualize a Self-Organizing Map. Finally we used real datasets
to understand what the Self-Organizing Map can tell us about labeled and unlabeled data. …

… dimensionality in scientific studies, such as concentration data for 40+ elements routinely …
The self-organizing map (SOM), also known as Kohonen neural network or Kohenen map (…

… the self-organizing maps (SOMs) or Kohonen map, thanks to its ability to emphasize underlying
behavior such as fault modes. An automatic fault mode detection is presented based on …