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NCA
2007
IEEE
15 years 3 months ago
Using evolution to improve neural network learning: pitfalls and solutions
: Autonomous neural network systems typically require fast learning and good generalization performance, and there is potentially a trade-off between the two. The use of evolutiona...
John A. Bullinaria
ESWA
2006
114views more  ESWA 2006»
15 years 4 months ago
Bankruptcy prediction with neural logic networks by means of grammar-guided genetic programming
The paper demonstrates the efficient use of hybrid intelligent systems for solving the classification problem of bankruptcy. The aim of the study is to obtain classification schem...
Athanasios Tsakonas, Georgios Dounias, Michael Dou...
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
15 years 7 months ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing
APIN
2000
87views more  APIN 2000»
15 years 3 months ago
The Architecture and Performance of a Stochastic Competitive Evolutionary Neural Tree Network
: A new dynamic tree structured network - the Stochastic Competitive Evolutionary Neural Tree (SCENT) is introduced. The network is able to provide a hierarchical classification of...
Neil Davey, Rod Adams, Stella J. George
AIA
2006
15 years 5 months ago
FPGA-Targeted Neural Architecture for Embedded Alertness Detection
Several recent works have used neural networks to discriminate vigilance states in humans from electroencephalographic (EEG) signals. Our study aims at being more exhaustive. It t...
Bernard Girau, Khaled Ben Khalifa