A hybrid approach of neural network and level-2 fuzzy set

© Springer-Verlag Berlin Heidelberg 2015. This paper presents a new high performance algorithm for the classification problems. The structure of A Hybrid Approach of Neural Network and Level-2 Fuzzy set, including two main processes. The first process of this structure is the learning algorithm. Thi...

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Main Authors:	Teyakome,J., Eiamkanitchat,N.
Format:	Article
Published:	Springer Verlag 2015
Subjects:	Industrial and Manufacturing Engineering
Online Access:	http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84923174532&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39105
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Institution:	Chiang Mai University

id	th-cmuir.6653943832-39105
record_format	dspace
spelling	th-cmuir.6653943832-391052015-06-16T08:01:36Z A hybrid approach of neural network and level-2 fuzzy set Teyakome,J. Eiamkanitchat,N. Industrial and Manufacturing Engineering © Springer-Verlag Berlin Heidelberg 2015. This paper presents a new high performance algorithm for the classification problems. The structure of A Hybrid Approach of Neural Network and Level-2 Fuzzy set, including two main processes. The first process of this structure is the learning algorithm. This step applied the combination of the multilayer perceptron neural network and the level-2 fuzzy set for learning. The outputs from learning process are fed to the classification process by using the K-nearest neighbor. The classification results on standard datasets show better accuracy than other high performance Neuro-Fuzzy methods. 2015-06-16T08:01:36Z 2015-06-16T08:01:36Z 2015-01-01 Article 18761100 2-s2.0-84923174532 10.1007/978-3-662-46578-3_86 http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84923174532&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39105 Springer Verlag
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Industrial and Manufacturing Engineering
spellingShingle	Industrial and Manufacturing Engineering Teyakome,J. Eiamkanitchat,N. A hybrid approach of neural network and level-2 fuzzy set
description	© Springer-Verlag Berlin Heidelberg 2015. This paper presents a new high performance algorithm for the classification problems. The structure of A Hybrid Approach of Neural Network and Level-2 Fuzzy set, including two main processes. The first process of this structure is the learning algorithm. This step applied the combination of the multilayer perceptron neural network and the level-2 fuzzy set for learning. The outputs from learning process are fed to the classification process by using the K-nearest neighbor. The classification results on standard datasets show better accuracy than other high performance Neuro-Fuzzy methods.
format	Article
author	Teyakome,J. Eiamkanitchat,N.
author_facet	Teyakome,J. Eiamkanitchat,N.
author_sort	Teyakome,J.
title	A hybrid approach of neural network and level-2 fuzzy set
title_short	A hybrid approach of neural network and level-2 fuzzy set
title_full	A hybrid approach of neural network and level-2 fuzzy set
title_fullStr	A hybrid approach of neural network and level-2 fuzzy set
title_full_unstemmed	A hybrid approach of neural network and level-2 fuzzy set
title_sort	hybrid approach of neural network and level-2 fuzzy set
publisher	Springer Verlag
publishDate	2015
url	http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84923174532&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39105
_version_	1681421594229997568

A hybrid approach of neural network and level-2 fuzzy set

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