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GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
13 years 8 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
13 years 11 months ago
A comparative study of evolutionary optimization techniques in dynamic environments
Genetic Algorithms have widely been used for solving optimization problems in stationary environments. In recent years, there has been a growing interest for investigating and imp...
Demet Ayvaz, Haluk Topcuoglu, Fikret S. Gürge...
GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
14 years 2 months ago
Soft memory for stock market analysis using linear and developmental genetic programming
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...
Garnett Carl Wilson, Wolfgang Banzhaf
BMCBI
2011
12 years 11 months ago
Proportion statistics to detect differentially expressed genes: a comparison with log-ratio statistics
Background: In genetic transcription research, gene expression is typically reported in a test sample relative to a reference sample. Laboratory assays that measure gene expressio...
Tracy L. Bergemann, Jason Wilson
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
13 years 11 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...