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» A parameter-less genetic algorithm
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136
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GECCO
2005
Springer
137views Optimization» more  GECCO 2005»
15 years 9 months ago
Constant generation for the financial domain using grammatical evolution
This study reports the work to date on the analysis of different methodologies for constant creation with the aim of applying the most advantageous method to the dynamic real wor...
Ian Dempsey
136
Voted
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
15 years 9 months ago
Meta-grammar constant creation with grammatical evolution by grammatical evolution
This study examines the utility of meta-grammar constant generation on a series of benchmark problems. The performance of the meta-grammar approach is compared to a grammar which ...
Ian Dempsey, Michael O'Neill, Anthony Brabazon
114
Voted
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 9 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
116
Voted
GECCO
2005
Springer
137views Optimization» more  GECCO 2005»
15 years 9 months ago
Effective image compression using evolved wavelets
Wavelet-based image coders like the JPEG2000 standard are the state of the art in image compression. Unlike traditional image coders, however, their performance depends to a large...
Uli Grasemann, Risto Miikkulainen
110
Voted
GECCO
2005
Springer
128views Optimization» more  GECCO 2005»
15 years 9 months ago
Evolutionary computation applied to the tuning of MEMS gyroscopes
We propose a tuning method for MEMS gyroscopes based on evolutionary computation to efficiently increase the sensitivity of MEMS gyroscopes through tuning and, furthermore, to fin...
Didier Keymeulen, Wolfgang Fink, Michael I. Fergus...