An Enhancement of a Learning Procedure in Neuro-Fuzzy Model

被引：0

作者：

Vlasenko, Alexander ^{[1
]}

Vynokurova, Olena ^{[2
,3
]}

Vlasenko, Nataliia ^{[4
]}

Bodyanskiy, Yevgeniy ^{[1
]}

机构：

[1] Kharkiv Natl Univ Radio Elect, Dept Artificial Intelligence, Kharkov, Ukraine

[2] Kharkiv Natl Univ Radio Elect, Kharkov, Ukraine

[3] IT Step Univ, Lvov, Ukraine

[4] Simon Kuznets Kharkiv Natl Univ Econ, Dept Informat & Comp Engn, Kharkov, Ukraine

来源：

2018 IEEE FIRST INTERNATIONAL CONFERENCE ON SYSTEM ANALYSIS & INTELLIGENT COMPUTING (SAIC) | 2018年

关键词：

time series; neuro-fuzzy; membership function; Gaussian; Mackey-Glass; NETWORKS; SYSTEM;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper we propose an extended version of the learning algorithm for the hybrid five-layer neuro-fuzzy model. Backpropagation algorithm has been applied to the first layer membership functions centers tuning. The experimental results have shown that introduced enhancement significantly improves accuracy in time-series prediction benchmark tests without significant performance cost.

引用

页码：169 / 172

页数：4

共 50 条

[21] Online neuro-fuzzy model learning of dynamic systems with measurement noise
Gu, Wen
Lan, Jianglin
Mason, Byron
NONLINEAR DYNAMICS, 2024, 112 (07) : 5525 - 5540
[22] A new hybrid neuro-fuzzy model with reinforcement learning for intelligent agents
Figueiredo, Karla
Pacheco, Marco
Vellasco, Marley
Souza, Flávio
Controle y Automacao, 2007, 18 (02): : 234 - 250
[23] An adaptive learning algorithm for a neuro-fuzzy network
Bodyanskiy, Yevgeniy
Kolodyazhniy, Vitaliy
Stephan, Andreas
COMPUTATIONAL INTELLIGENCE: THEORY AND APPLICATIONS, PROCEEDINGS, 2001, 2206 : 68 - 75
[24] Speech enhancement using adaptive neuro-fuzzy filtering
Thevaril, J
Kwan, HK
ISPACS 2005: PROCEEDINGS OF THE 2005 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATION SYSTEMS, 2005, : 753 - 756
[25] EVOLVING NEURO-FUZZY SYSTEM COMBINED LEARNING
Deineko, A. A.
Pliss, I. P.
Ye, Bodyanskiy
RADIO ELECTRONICS COMPUTER SCIENCE CONTROL, 2012, 1 : 86 - 92
[26] A self-learning neuro-fuzzy system
DeClaris, N
Su, MC
HYBRID SYSTEMS II, 1995, 999 : 106 - 127
[27] Evolutionary Learning of Flexible Neuro-Fuzzy Systems
Cpalka, Krzysztof
Rutkowski, Leszek
2008 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5, 2008, : 969 - 975
[28] Neuro-fuzzy learning with symbolic and numeric data
D. D. Nauck
Soft Computing, 2004, 8 : 383 - 396
[29] Improve neuro-fuzzy learning by attribute reduction
Chang, Fengming M.
Chan, Chien-Chung
2008 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1 AND 2, 2008, : 37 - 41
[30] Neuro-fuzzy modeling with a new hybrid learning
Amaral, TG
Crisóstomo, MM
Pires, VF
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, Vols 1and 2, 2004, : 882 - 887

← 1 2 3 4 5 →