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» An Effective Learning Method for Max-Min Neural Networks
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GECCO
2006
Springer
141views Optimization» more  GECCO 2006»
14 years 12 days ago
Coevolution of neural networks using a layered pareto archive
The Layered Pareto Coevolution Archive (LAPCA) was recently proposed as an effective Coevolutionary Memory (CM) which, under certain assumptions, approximates monotonic progress i...
German A. Monroy, Kenneth O. Stanley, Risto Miikku...
AES
2008
Springer
133views Cryptology» more  AES 2008»
13 years 8 months ago
Alternative neural networks to estimate the scour below spillways
Artificial neural networks (ANN's) are associated with difficulties like lack of success in a given problem and unpredictable level of accuracy that could be achieved. In eve...
H. Md. Azamathulla, M. C. Deo, P. B. Deolalikar
ITCC
2005
IEEE
14 years 2 months ago
Real Stock Trading Using Soft Computing Models
The main focus of this study is to compare different performances of soft computing paradigms for predicting the direction of individuals stocks. Three different artificial intell...
Brent Doeksen, Ajith Abraham, Johnson P. Thomas, M...
ACL
1998
13 years 10 months ago
Neural Network Recognition of Spelling Errors
One area in which artificial neural networks (ANNs) may strengthen NLP systems is in the identification of words under noisy conditions. In order to achieve this benefit when spel...
Mark Lewellen
ICANN
2011
Springer
13 years 6 days ago
Bias of Importance Measures for Multi-valued Attributes and Solutions
Attribute importance measures for supervised learning are important for improving both learning accuracy and interpretability. However, it is well-known there could be bias when th...
Houtao Deng, George C. Runger, Eugene Tuv