Expression Programming Techniques for Formulation of Structural Engineering Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Amir Hossein Gandomi and Amir Hossein Alavi",
  title =        "Expression Programming Techniques for Formulation of
                 Structural Engineering Systems",
  editor =       "Amir Hossein Gandomi and Xin-She Yang and 
                 Siamak Talatahari and Amir Hossein Alavi",
  booktitle =    "Metaheuristic Applications in Structures and
  publisher =    "Elsevier",
  address =      "Oxford",
  year =         "2013",
  chapter =      "18",
  pages =        "439--455",
  keywords =     "genetic algorithms, genetic programming, Gene
                 expression programming, Data mining, structural
                 engineering, expression programming, prediction",
  isbn13 =       "978-0-12-398364-0",
  DOI =          "doi:10.1016/B978-0-12-398364-0.00018-8",
  URL =          "",
  abstract =     "Modelling the real behaviour of structural systems is
                 very difficult because of the multivariable
                 dependencies of materials and structural responses. To
                 deal with this complex behavior, simplifying
                 assumptions are commonly incorporated into the
                 development of the conventional methods. This may lead
                 to very large errors. The present study investigates
                 the simulation capabilities of expression programming
                 (EP) techniques by applying them to complex structural
                 engineering problems. Gene expression programming (GEP)
                 and multiexpression programming (MEP) are the employed
                 EP systems. Compared with traditional genetic
                 programming, the EP techniques are more compatible with
                 computer architectures. This results in a significant
                 speedup in their execution. GEP and MEP are
                 substantially useful in deriving empirical models for
                 characterising the behavior of structural engineering
                 systems by directly extracting the knowledge contained
                 in the experimental data. The problems analysed herein
                 include the following: (i) prediction of shear strength
                 of reinforced concrete columns and (ii) prediction of
                 hysteretic energy demand in steel moment resisting
                 frames. The results obtained by GEP and MEP are
                 compared with those provided by other equations
                 presented in the literature and found to be more
                 accurate. The new approaches of GEP and MEP overcome
                 the shortcomings of different methods previously
                 presented in the literature for the analysis of
                 structural engineering systems. Contrary to artificial
                 neural networks and many other soft computing tools,
                 GEP and MEP provide reasonably simplified prediction
                 equations. The derived equations can be used for
                 routine design practice. Unlike the conventional
                 methods, GEP and MEP do not require any simplifying
                 assumptions in developing the models.",

Genetic Programming entries for A H Gandomi A H Alavi