Deterministic-Embedded Monte Carlo Approach to Find out an Objective Item in a Large Number of Data Sets

International Journal of Applied Physics and Mathematics ◽

10.17706/ijapm.2019.9.4.173-181 ◽

2019 ◽

Vol 9 (4) ◽

pp. 173-181

Author(s):

Xingbo Wang ◽

◽

Jianxiang Guo

Keyword(s):

Monte Carlo ◽

Data Sets ◽

Monte Carlo Approach ◽

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Derivation of minimum best sample size from microarray data sets: A Monte Carlo approach

2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) ◽

10.1109/cibcb.2011.5948461 ◽

2011 ◽

Author(s):

Chengpeng Bi ◽

Mara Becker ◽

Steve Leeder

Keyword(s):

Monte Carlo ◽

Sample Size ◽

Microarray Data ◽

Data Sets ◽

Monte Carlo Approach

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Wigner-Boltzmann Monte Carlo approach to nanodevice simulation: from quantum to semiclassical transport

Journal of Computational Electronics ◽

10.1007/s10825-009-0281-3 ◽

2009 ◽

Vol 8 (3-4) ◽

pp. 324-335 ◽

Author(s):

Damien Querlioz ◽

Huu-Nha Nguyen ◽

Jérôme Saint-Martin ◽

Arnaud Bournel ◽

Sylvie Galdin-Retailleau ◽

...

Keyword(s):

Monte Carlo ◽

Monte Carlo Approach ◽

Semiclassical Transport

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Relaxation dynamics in small clusters: A modified Monte Carlo approach

Journal of Computational Physics ◽

10.1016/j.jcp.2007.11.007 ◽

2008 ◽

Vol 227 (4) ◽

pp. 2666-2673 ◽

Author(s):

Barnana Pal

Keyword(s):

Monte Carlo ◽

Relaxation Dynamics ◽

Monte Carlo Approach ◽

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Uncertainty study on atmospheric dispersion simulations using meteorological ensembles with a Monte Carlo approach, applied to the Fukushima nuclear accident

Atmospheric Environment X ◽

10.1016/j.aeaoa.2021.100112 ◽

2021 ◽

pp. 100112

Author(s):

Ngoc Bao Tran LE ◽

Irène Korsakissok ◽

Vivien Mallet ◽

Raphaël Périllat ◽

Anne Mathieu

Keyword(s):

Monte Carlo ◽

Atmospheric Dispersion ◽

Nuclear Accident ◽

Fukushima Nuclear Accident ◽

Monte Carlo Approach

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A clustering-based biased Monte Carlo approach to protein titration curve prediction

2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA) ◽

10.1109/icmla51294.2020.00037 ◽

2020 ◽

Author(s):

Arun V. Sathanur ◽

Nathan A. Baker

Keyword(s):

Monte Carlo ◽

Titration Curve ◽

Monte Carlo Approach

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On the stochastic uncertainties of thermally and optically stimulated luminescence signals: A Monte Carlo approach

Journal of Luminescence ◽

10.1016/j.jlumin.2019.116945 ◽

2020 ◽

Vol 219 ◽

pp. 116945

Author(s):

Vasilis Pagonis ◽

Sebastian Kreutzer ◽

Alex Roy Duncan ◽

Ena Rajovic ◽

Christian Laag ◽

...

Keyword(s):

Monte Carlo ◽

Optically Stimulated Luminescence ◽

Monte Carlo Approach ◽

Stochastic Uncertainties

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A two-stage Monte Carlo approach to the expression of uncertainty with finite sample sizes

Proceedings of the 2005 IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement ◽

10.1109/amuem.2005.1594604 ◽

2005 ◽

Author(s):

S.V. Crowder ◽

R.D. Moyer

Keyword(s):

Monte Carlo ◽

Finite Sample ◽

Sample Sizes ◽

Two Stage ◽

Monte Carlo Approach ◽

Expression Of Uncertainty

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A Monte Carlo approach for maximum power estimation based on extreme value theory

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ◽

10.1109/43.992765 ◽

2002 ◽

Vol 21 (4) ◽

pp. 415-432 ◽

Author(s):

N.E. Evmorfopoulos ◽

G.I. Stamoulis ◽

J.N. Avaritsiotis

Keyword(s):

Monte Carlo ◽

Extreme Value Theory ◽

Power Estimation ◽

Value Theory ◽

Extreme Value ◽

Maximum Power ◽

Monte Carlo Approach

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Transient gas flow studied by a test particle Monte Carlo approach with ProVac3D

10.1063/1.4769632 ◽

2012 ◽

Author(s):

Xueli Luo ◽

Thomas Giegerich ◽

Christian Day

Keyword(s):

Monte Carlo ◽

Test Particle ◽

Gas Flow ◽

Monte Carlo Approach

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A sequential Monte Carlo approach to estimate biophysical neural models from spikes

Journal of Neural Engineering ◽

10.1088/1741-2560/8/6/065006 ◽

2011 ◽

Vol 8 (6) ◽

pp. 065006 ◽

Author(s):

Liang Meng ◽

Mark A Kramer ◽

Uri T Eden

Keyword(s):

Monte Carlo ◽

Sequential Monte Carlo ◽

Neural Models ◽

Monte Carlo Approach

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