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» Unsupervised Problem Decomposition Using Genetic Programming
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GECCO
2010
Springer
220views Optimization» more  GECCO 2010»
15 years 28 days ago
Interday foreign exchange trading using linear genetic programming
Foreign exchange (forex) market trading using evolutionary algorithms is an active and controversial area of research. We investigate the use of a linear genetic programming (LGP)...
Garnett Carl Wilson, Wolfgang Banzhaf
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
15 years 4 months ago
Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster
Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large n...
Kenneth Holladay
FUIN
2011
358views Cryptology» more  FUIN 2011»
14 years 1 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
GECCO
2008
Springer
104views Optimization» more  GECCO 2008»
14 years 10 months ago
Protein-protein functional association prediction using genetic programming
Determining if a group of proteins are functionally associated among themselves is an open problem in molecular biology. Within our long term goal of applying Genetic Programming ...
Beatriz García, Ricardo Aler, Agapito Ledez...
APIN
1998
98views more  APIN 1998»
14 years 9 months ago
The Evolution of Concurrent Programs
Process algebra are formal languages used for the rigorous specification and analysis of concurrent systems. By using a process algebra as the target language of a genetic program...
Brian J. Ross