Results 41 to 50 of about 7,538,728 (303)
EXACT SIMULATION OF A BOOLEAN MODEL
Image Analysis and Stereology, 2013 A Boolean model is a union of independent objects (compact random subsets) located at Poisson points. Two algorithms are proposed for simulating a Boolean model in a bounded domain. The first one applies only to stationary models.
Christian Lantuéjoul
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Statistics and Computing, 2001 Simulated annealing - moving from a tractable distribution to a distribution of interest via a sequence of intermediate distributions - has traditionally been used as an inexact method of handling isolated modes in Markov chain samplers. Here, it is shown how one can use the Markov chain transitions for such an annealing sequence to define an ...
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Research on Data-Driven Optimal Scheduling of Power System
Energies, 2023 The uncertainty of output makes it difficult to effectively solve the economic security dispatching problem of the power grid when a high proportion of renewable energy generating units are integrated into the power grid.
Jianxun Luo +4 more
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Importance sampling for multimodal functions and application to pricing exotic options.
, 2003 We consider importance sampling (IS) to increase the efficiency of Monte Carlo integration, especially for pricing exotic options where the random input is multivariate Normal.
Avramidis, Athanassios.N.
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Fourier Analysis of Stochastic Sampling Strategies for Assessing Bias and Variance in Integration [PDF]
, 2013 Each pixel in a photorealistic, computer generated picture is calculated by approximately integrating all the light arriving at the pixel, from the virtual scene. A common strategy to calculate these high-dimensional integrals is to average the estimates
Kautz, Jan, Subr, Katric
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, 2022 A prototype-based sampling method for spatial data sampling and its application in landslide susceptibility mapping
Prototype-based sampling (14190421)
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Advantage estimator based on importance sampling
Tongxin xuebao, 2019 In continuous action tasks,deep reinforcement learning usually uses Gaussian distribution as a policy function.Aiming at the problem that the Gaussian distribution policy function slows down due to the clipped action,an importance sampling advantage ...
Quan LIU, Yubin JIANG, Zhihui HU
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Applied Sciences, 2019 This paper concentrates on the capacity credit (CC) evaluation of wind energy, where a new method for constructing the joint distribution of wind speed and load is proposed.
Jilin Cai +3 more
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Support Vector Machine-Assisted Importance Sampling for Optimal Reliability Design
Applied Sciences, 2022 A population-based optimization algorithm combining the support vector machine (SVM) and importance sampling (IS) is proposed to achieve a global solution to optimal reliability design.
Chunyan Ling, Jingzhe Lei, Way Kuo
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Importance Sampling Spherical Harmonics [PDF]
Computer Graphics Forum, 2009 AbstractIn this paper we present the first practical method for importance sampling functions represented as spherical harmonics (SH). Given a spherical probability density function (PDF) represented as a vector of SH coefficients, our method warps an input point set to match the target PDF using hierarchical sample warping.
Wojciech Jarosz +2 more
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