A new multi-gene genetic programming approach to nonlinear system modeling. Part I: materials and structural engineering problems

@article{Gandomi2011ANM,
  title={A new multi-gene genetic programming approach to nonlinear system modeling. Part I: materials and structural engineering problems},
  author={Amir Hossein Gandomi and Amir Hossein Alavi},
  journal={Neural Computing and Applications},
  year={2011},
  volume={21},
  pages={171-187}
}
  • Amir Hossein Gandomi, Amir Hossein Alavi
  • Published 2011
  • Computer Science
  • Neural Computing and Applications
  • This paper presents a new approach for behavioral modeling of structural engineering systems using a promising variant of genetic programming (GP), namely multi-gene genetic programming (MGGP). MGGP effectively combines the model structure selection ability of the standard GP with the parameter estimation power of classical regression to capture the nonlinear interactions. The capabilities of MGGP are illustrated by applying it to the formulation of various complex structural engineering… CONTINUE READING

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    Applications of Computational Intelligence in Behavior Simulation of Concrete Materials