000019852 001__ 19852
000019852 005__ 20170118182339.0
000019852 04107 $$aeng
000019852 046__ $$k2017-01-09
000019852 100__ $$aManjarrez, Lino
000019852 24500 $$aNeuronal-Attenuation Laws for the Mexican Subduction: An Updating Effort

000019852 24630 $$n16.$$pProceedings of the 16th World Conference on Earthquake Engineering
000019852 260__ $$b
000019852 506__ $$arestricted
000019852 520__ $$2eng$$aThe most recent shaking experiences have demonstrated that the predictions of the seismic models are not always in agree with the registered responses. A deep examination of the current subduction attenuation laws for PGA (peak ground acceleration) has pointed out that most of them uses older information than fifteen years and the functions are not taking into consideration the latest source-station configurations and the aging of materials. In this paper a neural network NN that permits to estimate PGA (vertical, east-west and north-south components) via the magnitude M, the focal depth FD and the epicentral distance ED (as classes and numerical parameters), is presented. For constructing this renewed attenuation law, 1270 records collected from 1960 to 2015 at rock-like sites are considered. The obtained results show that calculated PGAs using the neuronal model are remarkably close to those recorded. The proposed attenuation curves are compared with Ground Motion Prediction Equations (GMPEs) using events from México, Japan, Chile and USA. This evaluation raises the question of regional dependence of ground-motion which is a highly debated issue. The results also show that the NN performs considerably better than the traditional equations so it could be considered as a good alternative in seismic hazard assessment.

000019852 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000019852 653__ $$aneural networks, subduction, peak ground acceleration, attenuation law, ground motion prediction equations

000019852 7112_ $$a16th World Conference on Earthquake Engineering$$cSantiago (CL)$$d2017-01-09 / 2017-01-13$$gWCEE16
000019852 720__ $$aManjarrez, Lino$$iAlcántara, Leonardo$$iGarcía, Silvia
000019852 8560_ $$ffischerc@itam.cas.cz
000019852 8564_ $$s1385452$$uhttps://invenio.itam.cas.cz/record/19852/files/455.pdf$$yOriginal version of the author's contribution as presented on USB, paper 455.
000019852 962__ $$r16048
000019852 980__ $$aPAPER