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» A hybrid approach to parameter tuning in genetic algorithms
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EVOW
2005
Springer
14 years 1 months ago
Self-Adapting Evolutionary Parameters: Encoding Aspects for Combinatorial Optimization Problems
Abstract. Evolutionary algorithms are powerful tools in search and optimization tasks with several applications in complex engineering problems. However, setting all associated par...
Marcos H. Maruo, Heitor S. Lopes, Myriam Regattier...
EVOW
2012
Springer
12 years 3 months ago
Applying (Hybrid) Metaheuristics to Fuel Consumption Optimization of Hybrid Electric Vehicles
This work deals with the application of metaheuristics to the fuel consumption minimization problem of hybrid electric vehicles (HEV) considering exactly specified driving cycles....
Thorsten Krenek, Mario Ruthmair, Günther R. R...
ML
2002
ACM
121views Machine Learning» more  ML 2002»
13 years 7 months ago
Choosing Multiple Parameters for Support Vector Machines
The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the gener...
Olivier Chapelle, Vladimir Vapnik, Olivier Bousque...
ACG
2006
Springer
14 years 1 months ago
RSPSA: Enhanced Parameter Optimization in Games
Most game programs have a large number of parameters that are crucial for their performance. Tuning these parameters by hand is rather difficult. Therefore automatic optimization a...
Levente Kocsis, Csaba Szepesvári, Mark H. M...
CMSB
2008
Springer
13 years 9 months ago
A Model Checking Approach to the Parameter Estimation of Biochemical Pathways
Model checking has historically been an important tool to verify models of a wide variety of systems. Typically a model has to exhibit certain properties to be classed `acceptable&...
Robin Donaldson, David Gilbert