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A Re-Examination of a Real World Blood Flow Modeling Problem Using Context-Aware Crossover

  • Hammad Majeed
  • Conor Ryan
Part of the Genetic and Evolutionary Computation book series (GEVO)

Abstract

This chapter describes context-aware crossover. This is an improved crossover technique for GP which always swaps subtrees into their best possible context in a parent. We show that this style of crossover is considerably more constructive than the standard method, and present several experiments to demonstrate how it operates, and how well it performs, before applying the technique to a real world application, the Blood Flow Modeling Problem.

Keywords

Genetic Program Real World Application Crossover Operator Good Individual Linear Scaling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Hammad Majeed
    • 1
  • Conor Ryan
    • 1
  1. 1.Department of Computer Science and Information SystemsUniversity of LimerickIreland

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