Radius Parallel Self-Organizing Map (RPSOM)

Classification of Streaming Fuzzy DEA Using Self-Organizing Map

The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...

Lifestyle patterns in the Iranian population: Self- organizing map application

Background: The present study evaluated the lifestyle behavior patterns and its associations with demographic factors in the Iranian population. Methods: A total of 8244 people aged 25-70 years who participated in a national survey in 2011 were included in the study. Factors related to lifestyle (such as diet, physical activity, and tobacco use) have been collected using a questionnaire. A sel...

A data partition method for parallel self-organizing map

We propose a method to partition training vectors into clusters for a parallel implementation of Self-organizing Map (SOM) algorithm The proposed algorithm assigns a cluster to a processor such that, in updating weights, the neighborhoods of a winning node in a cluster do not overlap the neighboring nodes of some winning nodes in other clusters. It reduces the overheads caused by synchronizatio...

Self-Organizing Map Convergence

Self-organizing maps are artificial neural networks designed for unsupervised machine learning. They represent powerful data analysis tools applied in many different areas including areas such as biomedicine, bioinformatics, proteomics, and astrophysics. We maintain a data analysis package in R based on self-organizing maps. The package supports efficient, statistical measures that enable the u...

Self-organizing map