Enhanced self organized dynamic tree neural network

Authors:
Juan F. De Paz;Sara Rodríguez;Ana Gil;Juan M. Corchado;Pastora Vega
Affiliations:
Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Year:
2010

Citing 12
Cited 0

Bayesian Ying-Yang machine, clustering and number of clusters

Pattern Recognition Letters - special issue on pattern recognition in practice V
Methods for Operations Planning in Airport Decision Support Systems

Applied Intelligence
Fuzzy referral based cooperation in social networks of agents

AI Communications
An enhanced self-organizing incremental neural network for online unsupervised learning

Neural Networks
Development of intelligent multisensor surveillance systems with agents

Robotics and Autonomous Systems
Techniques for clustering gene expression data

Computers in Biology and Medicine
Agent-based modelling and simulation for the analysis of social patterns

Pattern Recognition Letters
A fast algorithm for computing minimum routing cost spanning trees

Computer Networks: The International Journal of Computer and Telecommunications Networking
Integrating case-based planning and RPTW neural networks to construct an intelligent environment for health care

Expert Systems with Applications: An International Journal
Model of experts for decision support in the diagnosis of leukemia patients

Artificial Intelligence in Medicine
Self Organized Dynamic Tree Neural Network

IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
A weighted voting summarization of SOM ensembles

Data Mining and Knowledge Discovery

Quantified Score

Hi-index	0.00

Visualization

Abstract

Cluster analysis is a technique used in a variety of fields There are currently various algorithms used for grouping elements that are based on different methods including partitional, hierarchical, density studies, probabilistic, etc This article will present the ESODTNN neural network, an evolution of the SODTNN network, which facilitates the revision process by merging its operational process with dendrogram techniques, and enables the automatic detection of clusters in an increased number of situations.