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BEO-COVID: Decision making tool based on evaluation and optimisation of models in UPPAAL
Larsen, Kim Guldstrand
(PI)
Stoustrup, Jakob
(CoPI)
Jensen, Peter Gjøl
(Project Participant)
Mikučionis, Marius
(Project Participant)
Jørgensen, Kenneth Yrke
(Project Participant)
Muniz Rodriguez, Marco Antonio
(Project Participant)
Poulsen, Danny Bøgsted
(Project Participant)
Tschaikowski, Max
(Project Participant)
Artificial Intelligence and Machine Learning
AI for the People
CISS - Center for Embedded Software Systems
Distributed, Embedded and Intelligent Systems
The Technical Faculty of IT and Design
Department of Computer Science
Automation & Control
Department of Electronic Systems
Support
AAU Shared Services
IT-Services
Overview
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Facilities
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Press/Media
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Keyphrases
Anlysis
25%
Complex Scenarios
25%
COVID
50%
Danish Society
50%
Data-driven Modeling
50%
Decision Support
50%
Decision Support Tool
75%
Epidemiological Model
25%
Evaluation Model
50%
Fluid Model Checking
50%
Health Authorities
50%
Massive Parallelism
25%
Model Optimization
50%
Model Uncertainty
50%
Novo Nordisk
100%
School Reopening
50%
Sudden Change
50%
Supercomputer
25%
Superspreader Events
25%
Support Decision
50%
UPPAAL
100%
Engineering
Fluid Model
50%
Model Uncertainty
25%
Novo Nordisk
50%
Parallelism
25%
Statistical Model
50%
Stochastic Hybrid Model
50%
Sudden Change
25%