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Ağpak and Gökçen [11] developed new mathematical models for stochastic traditional and U-type assembly lines with a chance-constrained 0-1 integer programming technique.
One of the shortcomings of many available models for stochastic generation of daily rainfall data is that they are unable to preserve satisfactorily key statistical properties simultaneously at daily, monthly and annual time scales.
In this paper a hybrid of statistical (a Markov chain-gamma model for stochastic generation of rainfall and two different multivariate autoregressive models for stochastic generation of air temperature and influent time series in dry conditions) and conceptual modeling techniques is proposed for synthetic generation of influent time series.
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Some researchers presented a model for stochastic lead time.
In this area, there are some who prepared a model for stochastic demand and some who prepared a model for stochastic lead time.
In this area, there are some researchers who provided a model for stochastic demand.
Figure 1 Simulations of the proposed model for Stochastic scattering attenuation.
Leung and Wu (2004) proposed a robust optimization model for stochastic aggregate production planning.
This paper devotes to develop a computational model for stochastic analysis and reliability assessment of vehicle-track systems subject to earthquakes and track random irregularities.
We propose a model for stochastic hybrid systems (SHSs) where transitions between discrete modes are triggered by stochastic events much like transitions between states of a continuous-time Markov chains.
In this article, we present a computational model for stochastic simulation of the search process of TFs for their target sites on the DNA.
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