Articles | Volume 10, issue 12
Nat. Hazards Earth Syst. Sci., 10, 2527–2537, 2010
https://doi.org/10.5194/nhess-10-2527-2010
Nat. Hazards Earth Syst. Sci., 10, 2527–2537, 2010
https://doi.org/10.5194/nhess-10-2527-2010

Research article 07 Dec 2010

Research article | 07 Dec 2010

An attempt to model the relationship between MMI attenuation and engineering ground-motion parameters using artificial neural networks and genetic algorithms

G-A. Tselentis1 and L. Vladutu2 G-A. Tselentis and L. Vladutu
  • 1Seismological Laboratory, University of Patras, RIO 265 04, Patras, Greece
  • 2Mathematics Dept., Dublin City University, Dublin, Republic of Ireland

Abstract. Complex application domains involve difficult pattern classification problems. This paper introduces a model of MMI attenuation and its dependence on engineering ground motion parameters based on artificial neural networks (ANNs) and genetic algorithms (GAs). The ultimate goal of this investigation is to evaluate the target-region applicability of ground-motion attenuation relations developed for a host region based on training an ANN using the seismic patterns of the host region. This ANN learning is based on supervised learning using existing data from past earthquakes. The combination of these two learning procedures (that is, GA and ANN) allows us to introduce a new method for pattern recognition in the context of seismological applications. The performance of this new GA-ANN regression method has been evaluated using a Greek seismological database with satisfactory results.

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