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EVOW
2009
Springer
13 years 5 months ago
Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
Abstract. Evolutionary algorithms such as genetic programming and grammatical evolution have been used for simultaneously optimizing network architecture, variable selection, and w...
Stephen D. Turner, Marylyn D. Ritchie, William S. ...
IJACTAICIT
2010
163views more  IJACTAICIT 2010»
13 years 4 months ago
Modified Vector Field Histogram with a Neural Network Learning Model for Mobile Robot Path Planning and Obstacle Avoidance
In this work, a Modified Vector Field Histogram (MVFH) has been developed to improve path planning and obstacle avoidance for a wheeled driven mobile robot. It permits the detecti...
Bahaa I. Kazem, Ali H. Hamad, Mustafa M. Mozael
ARTMED
2002
121views more  ARTMED 2002»
13 years 7 months ago
An evolutionary artificial neural networks approach for breast cancer diagnosis
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
Hussein A. Abbass
OL
2011
177views Neural Networks» more  OL 2011»
12 years 10 months ago
Exploiting vector space properties to strengthen the relaxation of bilinear programs arising in the global optimization of proce
In this paper we present a methodology for finding tight convex relaxations for a special set of quadratic constraints given by bilinear and linear terms that frequently arise in ...
Juan P. Ruiz, Ignacio E. Grossmann
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
14 years 2 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull