000009443 001__ 9443
000009443 005__ 20141205150206.0
000009443 04107 $$aeng
000009443 046__ $$k2008-10-12
000009443 100__ $$aAtanasiu, Gabriela Maria
000009443 24500 $$aSeismic Risk Mitigation in Urban Areas Based on Artificial Intelligence Methods

000009443 24630 $$n14.$$pProceedings of the 14th World Conference on Earthquake Engineering
000009443 260__ $$b
000009443 506__ $$arestricted
000009443 520__ $$2eng$$aThis paper presents a GIS-based methodology for monitoring the seismic performance, while taking into account the deteriorations revealed during scenarios, aiming at the identification of the seismic serviceability of the structure. By using geospatial data, one can develop useful scenarios to improve the knowledge on structural vulnerability of the urban built infrastructure. Scenarios of modeling, simulation and nonlinear seismic analysis are described and applied to a class of damaged models for some of the structures typical of the existing urban infrastructure of Iaºi, Romania. Some data mining techniques, especially decision trees are presented as a tool for awareness and mitigation of seismic effects of possible future events in the urban area.

000009443 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000009443 653__ $$adata mining, seismic risk mitigation, urban areas management, geographic information systems

000009443 7112_ $$a14th World Conference on Earthquake Engineering$$cBejing (CN)$$d2008-10-12 / 2008-10-17$$gWCEE15
000009443 720__ $$aAtanasiu, Gabriela Maria$$iLeon, Florin$$iPopa, Bogdan
000009443 8560_ $$ffischerc@itam.cas.cz
000009443 8564_ $$s405423$$uhttps://invenio.itam.cas.cz/record/9443/files/09-01-0057.pdf$$yOriginal version of the author's contribution as presented on CD, Paper ID: 09-01-0057.
000009443 962__ $$r9324
000009443 980__ $$aPAPER