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GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
15 years 3 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
GECCO
2004
Springer
119views Optimization» more  GECCO 2004»
15 years 3 months ago
Learning Environment for Life Time Value Calculation of Customers in Insurance Domain
A critical success factor in Insurance business is its ability to use information sources and contained knowledge in the most effective way. Its profitability is obtained through t...
Andrea Tettamanzi, Luca Sammartino, Mikhail Simono...
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
15 years 1 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood
BMCBI
2010
146views more  BMCBI 2010»
14 years 10 months ago
Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers
Background: The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding pro...
Ross K. Shepherd, Theo H. E. Meuwissen, John A. Wo...
ISDA
2008
IEEE
15 years 4 months ago
Genetic Annealing Optimization: Design and Real World Applications
Both simulated annealing (SA) and the genetic algorithms (GA) are stochastic and derivative-free optimization technique. SA operates on one solution at a time, while the GA mainta...
Mostafa A. El-Hosseini, Aboul Ella Hassanien, Ajit...