Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Stephan Knapp"'
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 6, Pp 6631-6658 (2020)
Starting from a particle model we derive a macroscopic aggregation-diffusion equation for the evolution of slime mold under the assumption of propagation of chaos in the large particle limit. We analyze properties of the macroscopic model in the stat
Externí odkaz:
https://doaj.org/article/9596e74e18364cf9be40a84f70021b25
Autor:
Simone Göttlich, Stephan Knapp
Publikováno v:
Journal of Mathematics in Industry, Vol 10, Iss 1, Pp 1-21 (2020)
Abstract This paper is concerned with a simulation study for a stochastic production network model, where the capacities of machines may change randomly. We introduce performance measures motivated by risk measures from finance leading to a simulatio
Externí odkaz:
https://doaj.org/article/728e65ba6b79419d85e91c6862f68ded
Autor:
Simone Göttlich, Stephan Knapp
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 2, Pp 1677-1701 (2020)
We introduce a stochastic traffic flow model to describe random traffic accidents on a single road. The model is a piecewise deterministic process incorporating traffic accidents and is based on a scalar conservation law with space-dependent flux fun
Externí odkaz:
https://doaj.org/article/fbcf14bdab5f414e82dbca0457847b6f
Publikováno v:
Journal of Computational Dynamics. 7:243-269
A single queueing system with time-dependent exponentially distributed arrival processes and exponential machine processes (Kendall notation \begin{document}$ M_t/M_t/1 $\end{document} ) is analyzed. Modeling the time evolution for the discrete queue
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0386e9a745405eaf1b4ea1e6d1012c01
https://doi.org/10.3934/jcd.2020010
https://doi.org/10.3934/jcd.2020010
Autor:
Stephan Knapp, Simone Göttlich
Publikováno v:
SIAM Journal on Applied Mathematics. 79:1197-1217
In this paper, a production model based on (hyperbolic) differential equations with stochastic and load-dependent machine failures is introduced. We derive the model on the base of a well-established deterministic model and show its well-posedness. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43a5edfd8da734c6999bcfff59bdc1b0
https://doi.org/10.1137/18m1193177
https://doi.org/10.1137/18m1193177
Autor:
Stephan Knapp, Simone Göttlich
Publikováno v:
Crowd Dynamics, Volume 2 ISBN: 9783030504496
We present a data fitting approach for the social force model by Helbing and Molnar using artificial neural networks. The latter are used as a universal approximation for the unknown interaction forces between pedestrians. We train the artificial neu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3796aed768fd9155b58b3a6bd1bb846e
https://doi.org/10.1007/978-3-030-50450-2_2
https://doi.org/10.1007/978-3-030-50450-2_2
Publikováno v:
Kinetic & Related Models. 11:1333-1358
We investigate a stochastic model hierarchy for pedestrian flow. Starting from a microscopic social force model, where the pedestrians switch randomly between the two states stop-or-go, we derive an associated macroscopic model of conservation law ty
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a070537556e876e58b9e5024f69815f
https://doi.org/10.3934/krm.2018052
https://doi.org/10.3934/krm.2018052
Autor:
Simone Göttlich, Stephan Knapp
Publikováno v:
Discrete & Continuous Dynamical Systems - B. 22:3235-3258
In this paper, we focus on production network models based on ordinary and partial differential equations that are coupled to semi-Markovian failure rates for the processor capacities. This modeling approach allows for intermediate capacity states in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d9cb60d39185184eb17a7e29d4bc33f
https://doi.org/10.3934/dcdsb.2017090
https://doi.org/10.3934/dcdsb.2017090
Autor:
Simone Göttlich, Stephan Knapp
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 2, Pp 1677-1701 (2020)
We introduce a stochastic traffic flow model to describe random traffic accidents on a single road. The model is a piecewise deterministic process incorporating traffic accidents and is based on a scalar conservation law with space-dependent flux fun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84dc1d3f18b77c6af6c079aa0556e6d4
http://arxiv.org/abs/1907.13544
http://arxiv.org/abs/1907.13544
This article deals with the modeling for an individual car path through a road network, where the dynamics is driven by a coupled system of ordinary and partial differential equations. The network is characterized by bounded buffers at junctions that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70d9ac6592d6abb66f7743f404dea709
http://arxiv.org/abs/1905.12159
http://arxiv.org/abs/1905.12159