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APIN
2004
116views more  APIN 2004»
13 years 7 months ago
Neural Learning from Unbalanced Data
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
Yi Lu Murphey, Hong Guo, Lee A. Feldkamp
EOR
2006
73views more  EOR 2006»
13 years 7 months ago
Path relinking and GRG for artificial neural networks
Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is appr...
Abdellah El-Fallahi, Rafael Martí, Leon S. ...
ICIP
2003
IEEE
14 years 9 months ago
Non-linear 3D rendering workload prediction based on a combined fuzzy-neural network architecture for grid computing application
Although, computational Grid has been initially developed to solve large-scale scientific research problems, it is extended for commercial and industrial applications. An interest...
John K. Doulamis, Anastasios D. Doulamis
FLAIRS
2006
13 years 8 months ago
GFAM: Evolving Fuzzy ARTMAP Neural Networks
Fuzzy ARTMAP (FAM) is one of the best neural network architectures in solving classification problems. One of the limitations of Fuzzy ARTMAP that has been extensively reported in...
Ahmad Al-Daraiseh, Michael Georgiopoulos, Annie S....
ESANN
2008
13 years 9 months ago
Classification of chestnuts with feature selection by noise resilient classifiers
In this paper we solve the problem of classifying chestnut plants according to their place of origin. We compare the results obtained by state of the art classifiers, among which,...
Elena Roglia, Rossella Cancelliere, Rosa Meo