IMIOL: A SYSTEM FOR INDEXING IMAGES BY THEIR SEMANTIC CONTENT BASED ON POSSIBILISTIC FUZZY CLUSTERING AND ADAPTIVE RESONANCE THEORY NEURAL NETWORKS LEARNING

2010 ◽  
Vol 24 (9) ◽  
pp. 821-846 ◽  
Author(s):  
L. B. Romdhane ◽  
H. Bannour ◽  
B. Ayeb
Keyword(s):  
Neural Networks ◽  
Fuzzy Clustering ◽  
Semantic Content ◽  
Adaptive Resonance Theory ◽  
Resonance Theory ◽  
Adaptive Resonance

scholarly journals Neural Networks Art: Solving Problems with Multiple Solutions and New Teaching Algorithm

2014 ◽  
Vol 8 (1) ◽  
pp. 15-21
Author(s):  
Dmitrienko V. D ◽  
Yu. Zakovorotnyi A ◽  
Yu. Leonov S ◽  
Khavina I. P
Keyword(s):  
Neural Networks ◽  
Multiple Solutions ◽  
Input Data ◽  
Learning Algorithms ◽  
Adaptive Resonance Theory ◽  
Classification Methods ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Noisy Input ◽  
New Algorithms

A new discrete neural networks adaptive resonance theory (ART), which allows solving problems with multiple solutions, is developed. New algorithms neural networks teaching ART to prevent degradation and reproduction classes at training noisy input data is developed. Proposed learning algorithms discrete ART networks, allowing obtaining different classification methods of input.

scholarly journals Prediction of Resistance Spot Weld Quality of 780 MPa Grade Steel Using Adaptive Resonance Theory Artificial Neural Networks

Metals ◽  
2018 ◽  
Vol 8 (6) ◽  
pp. 453 ◽  
Author(s):  
Insung Hwang ◽  
Hyeonsang Yun ◽  
Jinyoung Yoon ◽  
Munjin Kang ◽  
Dongcheol Kim ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Adaptive Resonance Theory ◽  
Spot Weld ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Resistance Spot ◽  
Resistance Spot Weld ◽  
Grade Steel
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