Neuro-Fuzzy Kolmogorov’s Network for Time Series Prediction and Pattern Classification

Author(s):  
Yevgeniy Bodyanskiy ◽  
Vitaliy Kolodyazhniy ◽  
Peter Otto
2011 ◽  
Vol 15 (3) ◽  
pp. 279-288 ◽  
Author(s):  
Hossein Soleimani-B. ◽  
Caro Lucas ◽  
Babak N. Araabi

Author(s):  
CATHERINE VAIRAPPAN ◽  
SHANGCE GAO ◽  
ZHENG TANG ◽  
HIROKI TAMURA

A new version of neuro-fuzzy system of feedbacks with chaotic dynamics is proposed in this work. Unlike the conventional neuro-fuzzy, improved neuro-fuzzy system with feedbacks is better able to handle temporal data series. By introducing chaotic dynamics into the feedback neuro-fuzzy system, the system has richer and more flexible dynamics to search for near-optimal solutions. In the experimental results, performance and effectiveness of the presented approach are evaluated by using benchmark data series. Comparison with other existing methods shows the proposed method for the neuro-fuzzy feedback is able to predict the time series accurately.


2009 ◽  
Vol 72 (7-9) ◽  
pp. 1870-1877 ◽  
Author(s):  
Catherine Vairappan ◽  
Hiroki Tamura ◽  
Shangce Gao ◽  
Zheng Tang

2001 ◽  
Vol 15 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Z Zeng ◽  
H Yan ◽  
A.M.N Fu

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