demonstrated is that the convergence index captures the notion that a SOM has learned the multivariate distribution of a training …

temporal thresholds. The adopted method, the Neural Network Self-Organizing Maps (SOM), is able to single out groups of cities …. The second section explains the data which will be used for the analysis and describes the used SOM algorithm. The … characteristics. The conclusions discuss the nature of those patterns. Due to SOM implementation it has been possible to identify …

temporal thresholds. The adopted method, the Neural Network Self-Organizing Maps (SOM), is able to single out groups of cities …. The second section explains the data which will be used for the analysis and describes the used SOM algorithm. The … characteristics. The conclusions discuss the nature of those patterns. Due to SOM implementation it has been possible to identify …

different temporal thresholds. By means of the Neural Networks Self-Organizing Maps (SOM), the study has investigated and … singled out groups of cities with high internal resemblance. Due to SOM implementation it has been possible to identify twenty …

search process is made intelligent by incorporating self-organizing map (SOM). These techniques improve the basic model as …

in credit card fraud detection where outlier may be more interesting than common cases. Self-organizing Map (SOM) is …