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GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
14 years 11 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
15 years 4 months ago
Transition models as an incremental approach for problem solving in evolutionary algorithms
This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model in which parti...
Anne Defaweux, Tom Lenaerts, Jano I. van Hemert, J...
CORR
2007
Springer
83views Education» more  CORR 2007»
14 years 10 months ago
Simulation of Phase Combinations in Shape Memory Alloys Patches by Hybrid Optimization Methods
In this paper, phase combinations among martensitic variants in shape memory alloys patches and bars are simulated by a hybrid optimization methodology. The mathematical model is ...
Linxiang X. Wang, Roderick V. N. Melnik
EVOW
2009
Springer
14 years 8 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. ...
GECCO
2003
Springer
15 years 3 months ago
Enhancing the Performance of GP Using an Ancestry-Based Mate Selection Scheme
The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm bein...
Rodney Fry, Andrew M. Tyrrell