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GECCO
2009
Springer
164views Optimization» more  GECCO 2009»
13 years 8 months ago
Solving iterated functions using genetic programming
An iterated function f(x) is a function that when composed with itself, produces a given expression f(f(x))=g(x). Iterated functions are essential constructs in fractal theory and...
Michael D. Schmidt, Hod Lipson
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
13 years 8 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
TCBB
2011
13 years 5 months ago
Accurate Construction of Consensus Genetic Maps via Integer Linear Programming
—We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which...
Yonghui Wu, Timothy J. Close, Stefano Lonardi
GECCO
2011
Springer
274views Optimization» more  GECCO 2011»
13 years 2 months ago
Fuzzy dynamical genetic programming in XCSF
—A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to Neural Networks, and more recently Dynamical ...
Richard Preen, Larry Bull
CEC
2010
IEEE
13 years 2 months ago
Discriminating normal and cancerous thyroid cell lines using implicit context representation Cartesian genetic programming
Abstract— In this paper, we describe a method for discriminating between thyroid cell lines. Five commercial thyroid cell lines were obtained, ranging from non-cancerous to cance...
Michael A. Lones, Stephen L. Smith, Andrew T. Harr...