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Architecture-Oriented Agent-Based Simulations and Machine Learning Solution: The Case of Tsunami Emergency Analysis for Local Decision Makers

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50020380" target="_blank" >RIV/62690094:18450/23:50020380 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.mdpi.com/2078-2489/14/3/172" target="_blank" >https://www.mdpi.com/2078-2489/14/3/172</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/info14030172" target="_blank" >10.3390/info14030172</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Architecture-Oriented Agent-Based Simulations and Machine Learning Solution: The Case of Tsunami Emergency Analysis for Local Decision Makers

  • Original language description

    Tsunamis are a perilous natural phenomenon endangering growing coastal populations and tourists in many seaside resorts. Failures in responding to recent tsunami events stresses the importance of further research in building a robust tsunami warning system, especially in the &quot;last mile&quot; component. The lack of detail, unification and standardisation in information processing and decision support hampers wider implementation of reusable information technology solutions among local authorities and officials. In this paper, the architecture of a tsunami emergency solution is introduced. The aim of the research is to present a tsunami emergency solution for local authorities and officials responsible for preparing tsunami response and evacuation plans. The solution is based on a combination of machine learning techniques and agent-based modelling, enabling analysis of both real and simulated datasets. The solution is designed and developed based on the principles of enterprise architecture development. The data exploration follows the practices for data mining and big data analyses. The architecture of the solution is depicted using the standardised notation and includes components that can be exploited by responsible local authorities to test various tsunami impact scenarios and prepare plans for appropriate response measures.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/LTC20020" target="_blank" >LTC20020: Consolidating research in tsunami hazard through the application of systems approach</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    INFORMATION

  • ISSN

    2078-2489

  • e-ISSN

    2078-2489

  • Volume of the periodical

    14

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    20

  • Pages from-to

    "Article Number: 172"

  • UT code for WoS article

    000959155000001

  • EID of the result in the Scopus database

    2-s2.0-85151097369