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Frontiers of Structural and Civil Engineering >> 2020, Volume 14, Issue 3 doi: 10.1007/s11709-020-0623-6
The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for traditional masonry
. ISISE, Institute of Science and Innovation for Bio-Sustainability (IB-S), Department of Civil Engineering, University of Minho, Guimarães 4800-058, Portugal.. Department of Civil Engineering, University of Algarve, Faro 8005-139, Portugal.. RISCO, Department of Civil Engineering, University of Aveiro, Aveiro 3810-193, Portugal
Abstract
Keywords
Artificial Neural Networks ; seismic vulnerability ; masonry buildings ; damage estimation ; vulnerability curves
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