New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic - Couverture souple

Livre 74 sur 322: SpringerBriefs in Applied Sciences and Technology

Amezcua, Jonathan

 
9783319737720: New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic
Couverture souple
ISBN 10 : 3319737724 ISBN 13 : 9783319737720
Editeur : Springer, 2018

Synopsis

In this book a new model for data classification was developed. This new model is based on the competitive neural network Learning Vector Quantization (LVQ) and type-2 fuzzy logic. This computational model consists of the hybridization of the aforementioned techniques, using a fuzzy logic system within the competitive layer of the LVQ network to determine the shortest distance between a centroid and an input vector. This new model is based on a modular LVQ architecture to further improve its performance on complex classification problems. It also implements a data-similarity process for preprocessing the datasets, in order to build dynamic architectures, having the classes with the highest degree of similarity in different modules. Some architectures were developed in order to work mainly with two datasets, an arrhythmia dataset (using ECG signals) for classifying 15 different types of arrhythmias, and a satellite images segments dataset used for classifying six different types of soil. Both datasets show interesting features that makes them interesting for testing new classification methods.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Éditeur
Springer
Date d'édition
2018
Langue
anglais
ISBN 10 
3319737724
ISBN 13 
9783319737720
Reliure
Broché
Numéro d'édition
1
Nombre de pages
84
Coordonnées du fabricant
non disponible
Personne responsable
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Allemagne