Trajković, Slaviša

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  • Trajković, Slaviša (1)
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Author's Bibliography

Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks

Stojković, Milan; Marjanović, Dušan; Rakić, Dragan; Ivetić, Damjan; Simić, Višnja; Milivojević, Nikola; Trajković, Slaviša

(IWA Publishing, 2023) 

TY  - JOUR
AU  - Stojković, Milan
AU  - Marjanović, Dušan
AU  - Rakić, Dragan
AU  - Ivetić, Damjan
AU  - Simić, Višnja
AU  - Milivojević, Nikola
AU  - Trajković, Slaviša
PY  - 2023
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/3040
AB  - The objective of this research is to propose a novel framework for assessing the consequences of hazardous events on a water resources system using dynamic resilience. Two types of hazardous events were considered: a severe flood event and an earthquake. Given that one or both hazards have occurred and considering the intensity of those events, the main characteristics of flood
 dynamic resilience were evaluated. The framework utilizes an artificial neural network (ANN) to estimate dynamic resilience. The ANN was trained using a large, generated dataset that included a wide range of situations, from relatively mild hazards to severe ones. A case study was performed on the Pirot water system (Serbia). Dynamic resilience was derived from the developed system dynamics model alongside the hazardous models implemented. The most extreme hazard combination results in the robustness of 0.04, indicating a combination of an earthquake with a significant magnitude and a flood hydrograph with a low frequency of occurrence. In the case of moderate hazards, the system robustness has a median value of 0.2 and the rapidity median value of 162 h. The ANN’s efficacy was quantified using the average relative error metric which equals 2.14% and 1.77% for robustness and rapidity, respectively.
PB  - IWA Publishing
T2  - Journal of Hydroinformatics
T1  - Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks
DO  - 10.2166/hydro.2023.069
ER  - 
@article{
author = "Stojković, Milan and Marjanović, Dušan and Rakić, Dragan and Ivetić, Damjan and Simić, Višnja and Milivojević, Nikola and Trajković, Slaviša",
year = "2023",
abstract = "The objective of this research is to propose a novel framework for assessing the consequences of hazardous events on a water resources system using dynamic resilience. Two types of hazardous events were considered: a severe flood event and an earthquake. Given that one or both hazards have occurred and considering the intensity of those events, the main characteristics of flood
 dynamic resilience were evaluated. The framework utilizes an artificial neural network (ANN) to estimate dynamic resilience. The ANN was trained using a large, generated dataset that included a wide range of situations, from relatively mild hazards to severe ones. A case study was performed on the Pirot water system (Serbia). Dynamic resilience was derived from the developed system dynamics model alongside the hazardous models implemented. The most extreme hazard combination results in the robustness of 0.04, indicating a combination of an earthquake with a significant magnitude and a flood hydrograph with a low frequency of occurrence. In the case of moderate hazards, the system robustness has a median value of 0.2 and the rapidity median value of 162 h. The ANN’s efficacy was quantified using the average relative error metric which equals 2.14% and 1.77% for robustness and rapidity, respectively.",
publisher = "IWA Publishing",
journal = "Journal of Hydroinformatics",
title = "Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks",
doi = "10.2166/hydro.2023.069"
}
Stojković, M., Marjanović, D., Rakić, D., Ivetić, D., Simić, V., Milivojević, N.,& Trajković, S.. (2023). Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks. in Journal of Hydroinformatics
IWA Publishing..
https://doi.org/10.2166/hydro.2023.069
Stojković M, Marjanović D, Rakić D, Ivetić D, Simić V, Milivojević N, Trajković S. Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks. in Journal of Hydroinformatics. 2023;.
doi:10.2166/hydro.2023.069 .
Stojković, Milan, Marjanović, Dušan, Rakić, Dragan, Ivetić, Damjan, Simić, Višnja, Milivojević, Nikola, Trajković, Slaviša, "Assessment of water resources system resilience under hazardous events using system dynamic approach and artificial neural networks" in Journal of Hydroinformatics (2023),
https://doi.org/10.2166/hydro.2023.069 . .
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