A Genetic Algorithm for the Classification of Earthquake Damages in Buildings

  • Petros-Fotios Alvanitopoulos
  • Ioannis Andreadis
  • Anaxagoras Elenas
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 296)


In this paper an efficient classification system in the area of earthquake engineering is reported. The proposed method uses a set of artificial accelerograms to examine several types of damages in specific structures. With the use of seismic accelerograms, a set of twenty seismic parameters have been extracted to describe earthquakes. Previous studies based on artificial neural networks and neuro-fuzzy classification systems present satisfactory classification results in different types of earthquake damages. In this approach a genetic algorithm (GA) was used to find the optimal feature subset of the seismic parameters that minimizes the computational cost and maximizes the classification performance. Experimental results indicate that the use of the GA was able to classify the structural damages with classification rates up to 92%.


Genetic Algorithm Damage Index Seismic Signal Intensity Parameter Earthquake Damage 
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

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Petros-Fotios Alvanitopoulos
    • 1
  • Ioannis Andreadis
    • 1
  • Anaxagoras Elenas
    • 1
  1. 1.Democritus University of ThraceXanthiGreece

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