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» Training Neural Networks with GA Hybrid Algorithms
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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...
ICMCS
2005
IEEE
151views Multimedia» more  ICMCS 2005»
14 years 2 months ago
Face and Eye Rectification in Video Conference Using Artificial Neural Network
The lack of eye contact in video conference degrades the user’s experience. This problem has been known and studied for many years. There are hardware-based solutions to the eye...
Ben Yip
CIBCB
2009
IEEE
13 years 9 months ago
Improved prediction of trans-membrane spans in proteins using an artificial neural network
Tools for the identification of trans-membrane spans from the protein sequence are widely used in the experimental community. Computational structural biology seeks to increase the...
Julia Koehler, Ralf Mueller, Jens Meiler
FLAIRS
2004
13 years 10 months ago
Iterative Improvement of Neural Classifiers
A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...
GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
14 years 1 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui