Skip to Main content Skip to Navigation
New interface
Journal articles

Impact database application for natural and technological risk management

Abstract : Impact database development and application for risk analysis and management promote the usage of self-learning computer systems with elements of artificial intelligence. Such system learning could be successful when the databases store the complete information about each event, parameters of the simulation models, the range of its application, and residual errors. Each new description included in the database could increase the reliability of the results obtained with application of simulation models. The calibration of mathematical models is the first step to self-learning of automated systems. The article describes the events' database structure and examples of calibrated computer models as applied to the impact of expected emergencies and risk indicator assessment. Examples of database statistics usage in order to rank the subjects of the Russian Federation by the frequency of emergencies of different character as well as risk indicators are given.
Document type :
Journal articles
Complete list of metadata

https://hal-insu.archives-ouvertes.fr/insu-03706479
Contributor : Nathalie POTHIER Connect in order to contact the contributor
Submitted on : Tuesday, June 28, 2022 - 9:03:51 AM
Last modification on : Tuesday, June 28, 2022 - 9:03:52 AM
Long-term archiving on: : Monday, October 3, 2022 - 3:41:57 PM

File

nhess-20-95-2020.pdf
Publisher files allowed on an open archive

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Collections

Citation

Nina Frolova, Valery Larionov, Jean Bonnin, Sergey Suchshev, Alexander Ugarov, et al.. Impact database application for natural and technological risk management. Natural Hazards and Earth System Sciences, 2020, 20, pp.95-106. ⟨10.5194/nhess-20-95-2020⟩. ⟨insu-03706479⟩

Share

Metrics

Record views

15

Files downloads

3