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ICANN
2010
Springer
13 years 4 months ago
Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data
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...
Sandra García, Ricardo Aler, Inés Ma...
BIB
2008
109views more  BIB 2008»
13 years 6 months ago
Computational intelligence approaches for pattern discovery in biological systems
Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) ...
Gary B. Fogel
NPL
2006
113views more  NPL 2006»
13 years 6 months ago
A Back-propagation Neural Network Landmine Detector Using the Delta-technique and S-statistic
Landmines are a major problem facing the world today; there are millions of these deadly weapons still buried in various countries around the world. Humanitarian organizations dedi...
Taskin Koçak, Matthew Draper
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 26 days ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
ICONIP
2004
13 years 8 months ago
Collaborative Agent Learning Using Neurocomputing
In this paper we investigate techniques to train an agent to accomplish certain tasks. Artificial Neural Networks will be the technique used to the train the agent. This paper will...
Saulat Farooque, Ajith Abraham, Lakhmi C. Jain