498 search results - page 21 / 100 » Training Neural Networks with GA Hybrid Algorithms |
114
Voted
NCA
2008
IEEE
15 years 1 months ago
2008
IEEE
Motivated by the slow learning properties of multilayer perceptrons (MLPs) which utilize computationally intensive training algorithms, such as the backpropagation learning algorit...
208
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NCA
2011
IEEE
14 years 8 months ago
2011
IEEE
—Neural Networks have been an active research area for decades. However, privacy bothers many when the training dataset for the neural networks is distributed between two parties...
92
Voted
GECCO
2003
Springer
15 years 7 months ago
2003
Springer
We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic al...
CIMCA
2005
IEEE
15 years 7 months ago
2005
IEEE
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
GECCO
2004
Springer
15 years 7 months ago
2004
Springer
In this paper, we consider each neural network as a point in a multi-dimensional problem space and suggest a crossover that locates the central point of a number of neural networks...