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CORR
2010
Springer
150views Education» more  CORR 2010»
13 years 7 months ago
Extraction of Symbolic Rules from Artificial Neural Networks
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
S. M. Kamruzzaman, Md. Monirul Islam
TNN
1998
132views more  TNN 1998»
13 years 7 months ago
Synthesis of fault-tolerant feedforward neural networks using minimax optimization
—In this paper we examine a technique by which fault tolerance can be embedded into a feedforward network leading to a network tolerant to the loss of a node and its associated w...
Dipti Deodhare, M. Vidyasagar, S. Sathiya Keerthi
SCAI
2008
13 years 9 months ago
Defect Prediction in Hot Strip Rolling Using ANN and SVM
One of the largest factors affecting the loss for steel manufacturing are defects in the steel strips produced. Therefore the prediction of these defects forehand would be very im...
Manu Hietaniemi, Ulla Elsilä, Perttu Laurinen...
GECCO
2003
Springer
268views Optimization» more  GECCO 2003»
14 years 20 days ago
A Generalized Feedforward Neural Network Architecture and Its Training Using Two Stochastic Search Methods
Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks in which the synaptic interactions are mediated via a nonlinear mechanism called shuntin...
Abdesselam Bouzerdoum, Rainer Mueller
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
14 years 29 days ago
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
Yung-Keun Kwon, Byung Ro Moon