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» A hybrid approach to parameter tuning in genetic algorithms
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HAIS
2008
Springer
13 years 8 months ago
An Evolutionary Approach for Tuning Artificial Neural Network Parameters
The widespread use of artificial neural networks and the difficult work regarding the correct specification (tuning) of parameters for a given problem are the main aspects that mot...
Leandro M. Almeida, Teresa Bernarda Ludermir
CORR
2010
Springer
182views Education» more  CORR 2010»
13 years 7 months ago
SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization
The sequential parameter optimization (spot) package for R (R Development Core Team, 2008) is a toolbox for tuning and understanding simulation and optimization algorithms. Model-...
Thomas Bartz-Beielstein
NOLISP
2007
Springer
14 years 1 months ago
A Hybrid Genetic-Neural Front-End Extension for Robust Speech Recognition over Telephone Lines
This paper presents a hybrid technique combining the Karhonen-Loeve Transform (KLT), the Multilayer Perceptron (MLP) and Genetic Algorithms (GAs) to obtain less-variant Mel-freque...
Sid-Ahmed Selouani, Habib Hamam, Douglas D. O'Shau...
AIPRF
2008
13 years 9 months ago
Internal vs. External Parameters in Fitness Functions
A fitness function is needed for a Genetic Algorithm (GA) to work, and it appears natural that the combination of objectives and constraints into a single scalar function using ar...
Pedro A. Diaz-Gomez, Dean F. Hougen
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
Genetic algorithms for mentor-assisted evaluation function optimization
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an approp...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...