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Variable-free exploration of stochastic models: a gene regulatory network example.
Published 2007“…Finding coarse-grained, low-dimensional descriptions is an important task in the analysis of complex, stochastic models of gene regulatory networks. This task involves (a) identifying observables that best describe the state of these complex systems and (b) characterizing the dynamics of the observables. …”
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Coarse-graining molecular dynamics: stochastic models with non-Gaussian force distributions
Published 2019Journal article -
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Online stochastic modelling for network-based GPS real-time kinematic positioning
Published 2004“…Since it is too difficult for the functional model to define and/or handle the residual errors, an alternative approach that can be used is to account for these errors (and observation noise) within the stochastic model. In this study, an online stochastic modelling technique for network-based GPS RTK positioning is introduced to adaptively estimate the stochastic model in real time. …”
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Conference or Workshop Item -
108
Online Stochastic Modelling for Network-Based GPS Real-Time Kinematic Positioning
Published 2005“…Since it is too difficult for the functional model to define and/or handle the residual errors, an alternative approach that can be used is to account for these errors (and observation noise) within the stochastic model. In this study, an online stochastic modelling technique for network-based GPS RTK positioning is introduced to adaptively estimate the stochastic model in real time. …”
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Using stochastic model for lower financial risk management in refinery operation planning
Published 2010“…The results show that the stochastic model can forecast higher expected profit and lower risk compared to the deterministic model.…”
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Daily operation of Bukit Merah reservoir with stochastic dynamic programming under climate change impact
Published 2018Subjects: “…Stochastic models…”
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Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system
Published 2017“…This paper will examine the performance of 4-stage stochastic Runge-Kutta (SRK4) and specific stochastic Runge-Kutta (SRKS) methods with order 1.5 in approximating the solution of stochastic model in biological system. A comparative study of SRK4 and SRKS method will be presented in this paper. …”
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Reliable and efficient parameter estimation using approximate continuum limit descriptions of stochastic models
Published 2022“…One approach for overcoming this computational limitation is to coarse-grain the stochastic model to provide an approximate continuum model that can be solved using far less computational effort. …”
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A stochastic model for tumor control probability that accounts for repair from sublethal damage
Published 2017“…In this paper, we introduce a stochastic model for tumor response to radiotherapy which accounts for the effects of repair from sublethal damage. …”
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A stochastic model for the turbulent ocean heat flux under Arctic sea ice
Published 2025“…Furthermore, we show that the temperature in the upper layer of the Arctic ocean can be treated as a passive scalar during the whole year of SHEBA measurements. The stochastic model developed here provides a computationally inexpensive way to compute an observationally consistent PDF of this heat flux, and has implications for its parametrization in regional and global climate models.…”
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A stochastic model for the turbulent ocean heat flux under Arctic sea ice
Published 2021“…Furthermore, we show that the temperature in the upper layer of the Arctic ocean can be treated as a passive scalar during the whole year of SHEBA measurements. The stochastic model developed here provides a computationally inexpensive way to compute observationally consistent PDF of this heat flux, and has implications for its parametrization in regional and global climate models.…”
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