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» Weight initialization methods for multilayer feedforward
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BMCBI
2010
149views more  BMCBI 2010»
13 years 5 months ago
A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context
Background: Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex eti...
Ioannis K. Valavanis, Stavroula G. Mougiakakou, Ke...
IJON
2000
105views more  IJON 2000»
13 years 5 months ago
G-Prop: Global optimization of multilayer perceptrons using GAs
A general problem in model selection is to obtain the right parameters that make a model "t observed data. For a multilayer perceptron (MLP) trained with back-propagation (BP...
Pedro A. Castillo Valdivieso, Juan J. Merelo Guerv...
NPL
2000
112views more  NPL 2000»
13 years 5 months ago
Evolving Multilayer Perceptrons
Thispaper proposes anew version ofa method (G-Prop, geneticbackpropagation) that attempts to solve the problem of
Pedro A. Castillo Valdivieso, J. Carpio, Juan J. M...
AMC
2007
154views more  AMC 2007»
13 years 5 months ago
A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
The particle swarm optimization algorithm was showed to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become ve...
Jing-Ru Zhang, Jun Zhang, Tat-Ming Lok, Michael R....
ML
1998
ACM
136views Machine Learning» more  ML 1998»
13 years 5 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair