Self-Organizing Maps, Third Edition

@inproceedings{Kohonen2001SelfOrganizingMT,
  title={Self-Organizing Maps, Third Edition},
  author={T. Kohonen},
  booktitle={Springer Series in Information Sciences},
  year={2001}
}
  • T. Kohonen
  • Published in
    Springer Series in…
    2001
  • Computer Science
Exploring the socio-economic and environmental components of infectious diseases using multivariate geovisualization: West Nile Virus
TLDR
The use of geovisualization is proposed to provide a glimpse into the large number of potential variables influencing the disease and help distill them into a smaller number that might reveal hidden and unknown patterns that would be useful for developing future multilevel analytical models. Expand
Auscultating Diagnosis Support System by Using Self-Organizing Map: Analysis of Long-Term Recording Medical Body Sounds
TLDR
The recording of body sounds over a long term period is attempted and the result is that a SOM output is almost near areas (nodes) of the self-organizing map. Expand
Learning from accidents : human errors, preventive design and risk mitigation
Cartes auto-organisatrices pour la classification de données symboliques mixtes, de données de type intervalle et de données discrétisées.
Cette these s'inscrit dans le cadre de la classification automatique de donnees symboliques par des methodes geometriques bio-inspirees, plus specifiquement par les cartes auto-organisatrices. NousExpand
Machine learning and high-performance computing: Infrastructure and algorithms for the genome-scale study of genetic and epigenetic regulatory mechanisms with applications in neuroscience
TLDR
WASP is described, one of the first end-to-end systems to handle all aspects of NGS data generation, including sample submission, laboratory information management system (LIMS) functionality, and assay-specific processing pipelines, and two machine learning algorithms for the secondary analysis of ChIP-seq data. Expand
Swarm Intelligence Based Optimization
TLDR
A dynamic data clustering algorithm, called PSOFC, in which Particle Swarm Optimization is combined with the fuzzy c-means (FCM) clustering method to find the number of clusters and cluster centers concurrently is proposed. Expand
Fine-tuning of the SOMkNN classifier
TLDR
A fine-tuning for this SOMkNN classifier is proposed, which consists of a neuron relocation of the SOM map, which indicates a trend of classification rate improvement with the application of the fine tuning technique. Expand
Malware characteristics and threats on the internet ecosystem
TLDR
A classification framework that treats malware categorization as a supervised learning task, builds learning models with both support vector machines and decision trees and finally, visualizes classifications with self-organizing maps, which reveals that breeds in the categories of Trojan, Infector, Backdoor, and Worm significantly contribute to the malware population and impose critical risks on the Internet ecosystem. Expand
Hillslope chemical weathering across Paraná, Brazil: A data mining-GIS hybrid approach
article i nfo Self-organizing map (SOM) and geographic information system (GIS) models were used to investigate the nonlinear relationships associated with geochemical weathering processes at localExpand
Voice-pulse conversion method based on the response of the primary auditory cortex
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A sound-stimulus signal conversion interface for an auditory BMI that is based on the response of primary auditory cortex (A1) cells is developed that shows that the exponential processing was best. Expand
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