Self evolving Takagi-Sugeno-Kang fuzzy neural network.
Fuzzy neural networks is a popular combination in soft computing that unites the human-like reasoning style of fuzzy systems with the connectionist structure and learning ability of neural networks. There are two types of fuzzy neural networks, namely the Mamdani model, which is focused on interpret...
Main Author: | Nguyen Ngoc Nam |
---|---|
Other Authors: | Quek Hiok Chai |
Format: | Thesis |
Language: | English |
Published: |
2012
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/50807 |
Similar Items
-
Traffic prediction using a Generic Self-Evolving Takagi-Sugeno-Kang (GSETSK) fuzzy neural network
by: Nguyen, Ngoc Nam, et al.
Published: (2013) -
Self-evolving Takagi-Sugeno-Kangfuzzy neural network with self-evolving forgetting factor
by: Manpreet, Singh.
Published: (2013) -
The evolving Mamdani-Takagi-Sugeno neural-fuzzy inference system and its applications in the financial domain
by: Ho, Stanley Weng Luen.
Published: (2010) -
PENERAPAN METODE INFERENSI FUZZY TAKAGI-SUGENO-KANG UNTUK PREDIKSI PRODUKSI GETAH PINUS DI KPH KEDU SELATAN
by: , AULIA MARHADI, et al.
Published: (2013) -
Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems
by: Sunjie Zhang, et al.
Published: (2015-01-01)