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Soft Comput., 2013
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Gabor Rebner +3 more
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Gabor Rebner +3 more
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2022
This chapter looks into stochastic methods used to model different situations, which often involve using random numbers in one way or another. Methods like resampling and bootstrapping illustrate how flexible and widespread stochastic methods are. The main advantage of stochastic methods revolves around how it can allow working out useful stuff without
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This chapter looks into stochastic methods used to model different situations, which often involve using random numbers in one way or another. Methods like resampling and bootstrapping illustrate how flexible and widespread stochastic methods are. The main advantage of stochastic methods revolves around how it can allow working out useful stuff without
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Segmentation of Stochastic Images With a Stochastic Random Walker Method
IEEE Transactions on Image Processing, 2012We present an extension of the random walker segmentation to images with uncertain gray values. Such gray-value uncertainty may result from noise or other imaging artifacts or more general from measurement errors in the image acquisition process. The purpose is to quantify the influence of the gray-value uncertainty onto the result when using random ...
Torben Pätz, Tobias Preusser
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A stochastic improvement method for stochastic programming
Computational Statistics & Data Analysis, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Morita, Hiroshi, Ishii, Hiroaki
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Stochastic Methods for Production Processes
Economic Quality Control, 2004Summary: In two recent papers [\textit{E. von Collani}, ``Theoretical stochastics'' and ``Empirical stochastics'', in: E. v. Collani (ed.), Defining the science of stochastics. Lemgo: Heldermann Verlag. 147--174 and 175--213 (2004), contained in Zbl 1094.62005], Stochastics, the Science of Prediction is re-established, its basic concepts are developed ...
von Collani, Elart, Dumitrescu, Monica
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Stochastic Reduced Basis Methods
AIAA Journal, 2002Stochastic reduced basis methods for solving large-scale linear random algebraic systems of equations, such as those obtained by discretizing linear stochastic partial differential equations in space, time, and the random dimension, are introduced.
Nair, Prasanth B., Keane, Andrew J.
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Stochastic Methods in Transport Theory
Fusion Technology, 1998info:eu-repo/semantics ...
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A Method for Discrete Stochastic Optimization
Management Science, 1995This paper addresses the problem of optimizing a function over a finite or countably infinite set of alternatives, in situations where this objective function cannot be evaluated exactly, but has to be estimated or measured. A special focus is on situations where simulation is used to evaluate the objective function.
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Stochastic Network Planning Method
2009The success of the realisation of a project depends greatly on the efficiency of the planning phase. This study presents a new technology supporting the planning phase.
Zsolt Tibor Kosztyán, Judit Kiss
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The Stochastic Ray Method for Radiosity
1995This paper solves the system of radiosity equations with a stochastic numerical approach. Due to the high complexity of the problem for highly complex scenes, a stochastic variation of Jacobi iteration is developed which converges stochastically to the correct solution.
László Neumann +6 more
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