Abstract The Growing Hierarchical Self-Organizing Map (GHSOM) algorithm has shown its
potential for performing several tasks such as exploratory analysis, anomaly detection and …

Despite the popularity of Failure Mode and Effect Analysis (FMEA) in a wide range of
industries, two well-known shortcomings are the complexity of the FMEA worksheet and its …

A system for updating a database comprises an input interface and a processor. The input
interface is configured to receive image data. The processor is configured to determine from …

Artificial neural network, recently, is considered as a vibrant area in machine learning.
Particularly, Growing Hierarchical Self Organizing Map (GHSOM) model, as an intelligent …

Depuis son introduction en 1982, la carte auto-organisatrice de Kohonen (Self-Organizing
Map: SOM) a prouvé ses capacités de classification et visualisation des données …

Abstract The Evolving tree (ETree) is a hierarchical clustering and visualization model that
allows the number of clusters to grow and evolve with new data samples in an online …

This paper describes recent results achieved in the analysis of geo-distributed sensor data
generated in the context of the energy sector. The approaches described have roots in the …

Considering that growing hierarchical self-organizing map (GHSOM) ignores the influence
of individual component in sample vector analysis, and its accurate rate in detecting …

Resolving a discrepancy between disparate data sources is disclosed. Listing data for an
item for sale is received from a plurality of disparate data sources. The listing data is …

Abstract The Self-Organizing Map (SOM) is a popular neural network model for clustering
and visualization problems. However, it suffers from two major limitations, viz.,(1) it does not …