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pro vyhledávání: '"Thomas Krak"'
Autor:
Thomas Krak
Publikováno v:
Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications ISBN: 9783030805418
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee52e359e98cad54cca3a7c54373221a
https://doi.org/10.1007/978-3-030-80542-5_12
https://doi.org/10.1007/978-3-030-80542-5_12
Autor:
Thomas Krak
Publikováno v:
Optimization Under Uncertainty with Applications to Aerospace Engineering ISBN: 9783030601652
Stochastic processes in general provide a popular framework for modelling uncertainty about the evolution of dynamical systems. The theory of Markov chains uses a number of crucial assumptions about the (in)dependence of such a process on its history
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe4f23e62035b57dade2cbef5c15d24c
https://doi.org/10.1007/978-3-030-60166-9_5
https://doi.org/10.1007/978-3-030-60166-9_5
Publikováno v:
Uncertainty Modelling in Data Science
Advances in Intelligent Systems and Computing ISBN: 9783319975467
SMPS
Advances in Intelligent Systems and Computing
Advances in Intelligent Systems and Computing-Uncertainty Modelling in Data Science
UNCERTAINTY MODELLING IN DATA SCIENCE
Advances in Intelligent Systems and Computing ISBN: 9783319975467
SMPS
Advances in Intelligent Systems and Computing
Advances in Intelligent Systems and Computing-Uncertainty Modelling in Data Science
UNCERTAINTY MODELLING IN DATA SCIENCE
We consider the problem of estimating the transition rate matrix of a continuous-time Markov chain from a finite-duration realisation of this process. We approach this problem in an imprecise probabilistic framework, using a set of prior distribution
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030297640
ECSQARU
Symbolic and Quantitative Approaches to Reasoning with Uncertainty-15th European Conference, ECSQARU 2019, Belgrade, Serbia, September 18-20, 2019, Proceedings
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Symbolic and Quantitative Approaches to Reasoning with Uncertainty
ECSQARU
Symbolic and Quantitative Approaches to Reasoning with Uncertainty-15th European Conference, ECSQARU 2019, Belgrade, Serbia, September 18-20, 2019, Proceedings
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Symbolic and Quantitative Approaches to Reasoning with Uncertainty
We present an algorithm that can efficiently compute a broad class of inferences for discrete-time imprecise Markov chains, a generalised type of Markov chains that allows one to take into account partially specified probabilities and other types of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1819f1e2da9b4bf7dd96eff8c568595
https://doi.org/10.1007/978-3-030-29765-7_38
https://doi.org/10.1007/978-3-030-29765-7_38
Publikováno v:
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
Continuous-time Markov chains are mathematical models that are used to describe the state-evolution of dynamical systems under stochastic uncertainty, and have found widespread applications in various fields. In order to make these models computation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7d1d92fcf7814499b08489408ca6b98