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Overcoming Challeng...
Overcoming Challenges for Estimating Virus Spread Dynamics from Data
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- Vrabac, Damir (författare)
- KTH,Reglerteknik
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- Pare, Philip E. (författare)
- KTH,Reglerteknik
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- Sandberg, Henrik (författare)
- KTH,Reglerteknik
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- Johansson, Karl H., 1967- (författare)
- KTH,Reglerteknik
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2020
- 2020
- Engelska.
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Ingår i: Proceedings of the 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020. - : Institute of Electrical and Electronics Engineers (IEEE).
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In this paper we investigate estimating the parameters of a discrete time networked virus spread model from time series data. We explore the effect of multiple challenges on the estimation process including system noise, missing data, time-varying network structure, and quantization of the measurements. We also demonstrate how well a heterogeneous model can be captured by homogeneous model parameters. We further illustrate these challenges by employing recent data collected from the ongoing 2019 novel coronavirus (2019-nCoV) outbreak, motivating future work.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)