Téléchargez le livre : New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic

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

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Springer


Collection :

SpringerBriefs in Applied Sciences and Technology

Paru le : 2018-02-05

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Description

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 ofsoil. Both datasets show interesting features that makes them interesting for testing new classification methods.
 
Pages
73 pages
Collection
SpringerBriefs in Applied Sciences and Technology
Parution
2018-02-05
Marque
Springer
EAN papier
9783319737720
EAN PDF
9783319737737
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
7
Taille du fichier
2212 Ko
Prix
52,74 €

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