CORDIS Project
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This project focuses on developing advanced mathematical frameworks for creating dynamic models used in various applications such as Industry 4.0 and eHealth. It aims to improve the accuracy and reliability of system identification methods by addressing existing optimization challenges.
To obtain data-driven dynamic models for simulation, prediction, monitoring, classification or control tasks, in applications e.g. in Industry 4.0 and eHealth, most identification methods ‘solve’ an optimization problem, relying on some nonlinear iterative algorithm.
Undeniably, too many heuristics prevail:
What do we mean by ‘solved’?
Where did the algorithm converge to?
Is the model globally optimal, unique and reproducible?
To tackle these scientific deficiencies, we design a framework to de…
KATHOLIEKE UNIVERSITEIT LEUVEN
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