152 search results - page 6 / 31 » Training neural networks with noisy data as an ill-posed pro... |
ICANN
2009
Springer
14 years 17 hour ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
ESANN
2003
13 years 8 months ago
2003
This paper presents our approach to the rule extraction problem from trained neural network. A method called REX is briefly described. REX acquires a set of fuzzy rules using an ev...
ANSS
1998
IEEE
13 years 11 months ago
1998
IEEE
In solving application problems, the data sets used to train a neural network may not be hundred percent precise but within certain ranges. Representing data sets with intervals, ...
ICANN
2010
Springer
13 years 4 months ago
2010
Springer
The aim of this paper is to study the use of Evolutionary Multiobjective Techniques to improve the performance of Neural Networks (NN). In particular, we will focus on classificati...
BMCBI
2006
13 years 7 months ago
2006
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...