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The SIMBAD project aims to improve air traffic management performance evaluation through advanced machine learning techniques. It focuses on enhancing microsimulation models to better estimate variables and classify traffic patterns for strategic assessments.
The development of performance modelling methodologies able translate new ATM concepts and technologies into their impact on high-level, system wide KPIs has been a long-time objective of the ATM research community.
Bottom-up, microsimulation models are often the only feasible approach to address this problem in a reliable manner.
However, the practical application of large-scale simulation models to strategic ATM performance assessment is often hindered by their computational complexity.
The go…
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Greece, PIRAEUS
Type: University / higher education
Activity type: Higher or Secondary Education Establishments
SME: No
Spain, Barcelona
Type: University / higher education
Activity type: Higher or Secondary Education Establishments
SME: No
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