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Surrogate model / Likelihood function / Dimensional analysis / Maximum likelihood / Expectation–maximization algorithm / Statistics / Estimation theory / Kriging


X-TMCMC: Adaptive kriging for Bayesian inverse modeling
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Document Date: 2015-03-12 11:25:52


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File Size: 1,54 MB

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Company

Engineering Laboratory / The star / Elsevier B.V. / /

Country

Switzerland / /

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Facility

University of Thessaly / /

IndustryTerm

maximum length chain / time-to-solution / bounded pattern-search method / inference tools / stochastic optimization algorithms / proposed surrogated algorithms / neural networks / proposed kriging algorithm / parallel computing architectures / parallel numerical differentiation tools / web version / /

OperatingSystem

Petros / /

Organization

University of Thessaly / Department of Mechanical Engineering / /

Person

Panagiotis Angelikopoulos / Costas Papadimitriou / /

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Position

Prime Minister / leader / computer worker / Corresponding author / /

ProgrammingLanguage

J / R / C / /

Technology

proposed surrogated algorithms / KL-TMCMC algorithms / TMCMC algorithm / proposed kriging algorithm / load balancing / Gradient evaluations Comments TMCMC K-TMCMC No Yes No No L-TMCMC No Yes KL-TMCMC Yes Yes Basic algorithm / SA algorithms / kriging algorithm / stochastic optimization algorithms / K-TMCMC algorithm / TMCMC algorithms / L-TMCMC algorithm / proposed algorithms / MCMC algorithm / Basic TMCMC algorithm / simulation / TMCMC algorithm The TMCMC algorithm / MH algorithm / X-TMCMC algorithms / PDF / MCMC algorithms / /

URL

www.sciencedirect.com / www.elsevier.com/locate/cma / http /

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