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- W3186264865 abstract "This paper proposes a comparative study on the predictive accuracy of some classical system identification techniques with respect to recent learning-based approaches. The comparison is made on three case studies in the paradigm of Cyber-Physical Systems: a bilinear model whose parameters are derived from a real building experimental setup; an F-16 aircraft benchmark based on ground vibration experimental test data (with unknown model); a climate control experimental setup in a real building of the University of L’Aquila (with unknown model). For each case study, we compare diverse approaches producing predictive models of heterogeneous classes, whose accuracy is tested over a fixed time horizon. A discussion on the trade-off between predictive accuracy and model complexity is proposed with control applications in mind." @default.
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- W3186264865 date "2021-06-22" @default.
- W3186264865 modified "2023-09-26" @default.
- W3186264865 title "A Comparison of Classical Identification and Learning-Based Techniques for Cyber-Physical Systems" @default.
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- W3186264865 doi "https://doi.org/10.1109/med51440.2021.9480333" @default.
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