Earthquakes and Structures

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Multiple linear regression and fuzzy linear regression based assessment of postseismic structural damage indices

  • Fani I. Gkountakou (Department of Civil Engineering, Institute of Mathematics and Informatics, Democritus University of Thrace) ;
  • Anaxagoras Elenas (Department of Civil Engineering, Institute of Structural Statics and Dynamics, Democritus University of Thrace) ;
  • Basil K. Papadopoulos (Department of Civil Engineering, Institute of Mathematics and Informatics, Democritus University of Thrace)
  • Received : 2022.07.22
  • Accepted : 2023.05.14
  • Published : 2023.06.25
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Abstract

This paper studied the prediction of structural damage indices to buildings after earthquake occurrence using Multiple Linear Regression (MLR) and Fuzzy Linear Regression (FLR) methods. Particularly, the structural damage degree, represented by the Maximum Inter Story Drift Ratio (MISDR), is an essential factor that ensures the safety of the building. Thus, the seismic response of a steel building was evaluated, utilizing 65 seismic accelerograms as input signals. Among the several response quantities, the focus is on the MISDR, which expresses the postseismic damage status. Using MLR and FLR methods and comparing the outputs with the corresponding evaluated by nonlinear dynamic analyses, it was concluded that the FLR method had the most accurate prediction results in contrast to the MLR method. A blind prediction applying a set of another 10 artificial accelerograms also examined the model's effectiveness. The results revealed that the use of the FLR method had the smallest average percentage error level for every set of applied accelerograms, and thus it is a suitable modeling tool in earthquake engineering.

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