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Analysis of structural-damage predictions caused by an earthquake to identify areas with high damage levels

Abstract:

Methods, systems, and computer programs are presented for determining cluster areas within a region having higher estimates of damage caused by an earthquake as compared to damage in nearby areas. One method includes operations for identifying features associated with buildings within the region, and for training a machine learning program based on the identified features and earthquake damage data. In addition, the method includes operations for estimating, by the machine learning program, block damage caused by an earthquake, and for identifying a critical damage area (CDA) within the region. The CDA comprises a plurality of blocks geographically clustered that have a highest value of block damage. Additionally, the method includes an operation for causing presentation of the CDA within a map of the region.