ACROPOLIS: a graphical user interface for classification of risk for off-stream reservoirs using machine learning
Potential risk identification due to off-stream reservoir failure typically requires the use of two-dimensional hydraulic models, which demands considerable effort in terms of expertise, time and financial resources. Unfortunately, not all reservoir owners have access to these resources, and the pro...
| Authors: | , , |
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| Format: | article |
| Publication Date: | 2024 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/407125 |
| Online Access: | https://hdl.handle.net/2117/407125 https://dx.doi.org/10.1016/j.softx.2024.101657 |
| Access Level: | Open access |
| Keyword: | Dam failures -- Risk assessment Off-stream reservoir Potential risk Machine learning Dam break Preses (Enginyeria) -- Ruptura Àrees temàtiques de la UPC::Enginyeria civil::Enginyeria hidràulica, marítima i sanitària::Embassaments i preses |
| Summary: | Potential risk identification due to off-stream reservoir failure typically requires the use of two-dimensional hydraulic models, which demands considerable effort in terms of expertise, time and financial resources. Unfortunately, not all reservoir owners have access to these resources, and the process of assessing hazard classifications for administrations can be burdensome. ACROPOLIS was developed to address this challenge, employing a Machine Learning model to provide a preliminary risk classification according to Spanish regulations for off-stream reservoirs without the necessity of building a hydraulic model. This approach has been integrated into a user-friendly interface, simplifying the process for users. |
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