Abstract
Assessing impacts of threats to critical infrastructures is challenging due to the high
complexity. Using probabilistic simulations seems adequate to capture the uncertainty but makes it at the same time more challenging to compare different situations. Such comparison is particularly important when actions for improved protection are considered. We here propose a simulation that gives a probability distribution over a (finite) set of states and to compare the probability distributions in such a way that actions with lower chance of worst-case damage are preferred. The approach is illustrated with
data from the H2020 project PRECINCT where the impact of a flooding on a city is investigated.
complexity. Using probabilistic simulations seems adequate to capture the uncertainty but makes it at the same time more challenging to compare different situations. Such comparison is particularly important when actions for improved protection are considered. We here propose a simulation that gives a probability distribution over a (finite) set of states and to compare the probability distributions in such a way that actions with lower chance of worst-case damage are preferred. The approach is illustrated with
data from the H2020 project PRECINCT where the impact of a flooding on a city is investigated.
Original language | American English |
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Title of host publication | 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14) |
Number of pages | 8 |
Publication status | Published - 2023 |
Event | 14th International Conference on Applications of Statistics and Probability in Civil Engineering - Trinity College Dublin, Dublin, Ireland Duration: 9 Jul 2023 → 13 Jul 2023 Conference number: 14 https://icasp14.com/ |
Conference
Conference | 14th International Conference on Applications of Statistics and Probability in Civil Engineering |
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Abbreviated title | ICASP14 |
Country/Territory | Ireland |
City | Dublin |
Period | 9/07/23 → 13/07/23 |
Internet address |
Research Field
- Dependable Systems Engineering