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: | , |
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| Format: | Article |
| Published: |
Springer Verlag
2015
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| Subjects: | |
| 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 |
| Summary: | © 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. |
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