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Communication Dans Un Congrès Année : 2021

Seamless Simulations of Earthquake Disasters and Economy at 1:1 scale Utilizing Big-data

Résumé

We present a novel approach for utilizing big data to estimate economic impacts of disasters by performing end-to-end simulations of disasters and economy at 1:1 scale. In order to realize such fine-grained economic simulations, we developed a high-performance computing extension for Agent Based Economic Models (ABEMs) and seamlessly integrated it with a physics-based earthquake disaster simulator. Due to the lack of availability of the data of each individual economic entity, we generated data for 127 million agents by disaggregating the macroeconomic data available from several Japanese government agencies. Using the generated large data set, the ABEM is validated for the Japanese economy by reproducing past observations. As a demonstrative application of the developed system, we estimate the economic impacts of a disaster in Hanshin industrial region caused by a potential Nankai-trough mega-thrust earthquake, and the disaster hit economy is compared with normal state of the economy up to a period of 3 years.

Dates et versions

hal-03677307 , version 1 (24-05-2022)

Identifiants

Citer

Amit Gill, Maddegedara Lalith, Yoshiki Ogawa, Hideyuki O-Tani, Tsuyoshi Ichimura, et al.. Seamless Simulations of Earthquake Disasters and Economy at 1:1 scale Utilizing Big-data. WI-IAT '21: IEEE/WIC/ACM International Conference on Web Intelligence, Dec 2021, Melbourne VIC, Australia. pp.101-108, ⟨10.1145/3498851.3498937⟩. ⟨hal-03677307⟩
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