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» A class of instantaneously trained neural networks
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ENGL
2008
98views more  ENGL 2008»
13 years 7 months ago
A New Wavelet Back Propagation Neural Networks for Structural Dynamic Analysis
dynamic analysis of structures for earthquake induced loads is very expensive in terms of the computational burden. In this study, to reduce the computational effort a new neural s...
R. Kamyab Moghadas, S. Gholizadeh
IJCAI
1989
13 years 8 months ago
Training Feedforward Neural Networks Using Genetic Algorithms
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
David J. Montana, Lawrence Davis
TSMC
2002
119views more  TSMC 2002»
13 years 7 months ago
A cloning approach to classifier training
The Al-Alaoui algorithm is a weighted mean-square error (MSE) approach to pattern recognition. It employs cloning of the erroneously classified samples to increase the population o...
M. A. Al-Alaoui, R. Mouci, M. M. Mansour, Rony Fer...
TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
MICAI
2010
Springer
13 years 5 months ago
Combining Neural Networks Based on Dempster-Shafer Theory for Classifying Data with Imperfect Labels
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
Mahdi Tabassian, Reza Ghaderi, Reza Ebrahimpour