Determination of near-fault impulsive signals with multivariate naïve Bayes method

Deniz Ertuncay () and Giovanni Costa
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Deniz Ertuncay: University of Trieste
Giovanni Costa: University of Trieste

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 108, issue 2, No 17, 1763-1780

Abstract: Abstract Near-fault ground motions may contain impulse behavior on velocity records. To calculate the probability of occurrence of the impulsive signals, a large dataset is collected from various national data providers and strong motion databases. The dataset has a large number of parameters which carry information on the earthquake physics, ruptured faults, ground motion parameters, distance between the station and several parts of the ruptured fault. Relation between the parameters and impulsive signals is calculated. It is found that fault type, moment magnitude, distance and azimuth between a site of interest and the surface projection of the ruptured fault are correlated with the impulsiveness of the signals. Separate models are created for strike-slip faults and non-strike-slip faults by using multivariate naïve Bayes classifier method. Naïve Bayes classifier allows us to have the probability of observing impulsive signals. The models have comparable accuracy rates, and they are more consistent on different fault types with respect to previous studies.

Keywords: Near-fault ground motion; Velocity pulse; Impulsive signal; Probability of pulse occurrence (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11069-021-04755-0

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