Results 271 to 280 of about 708,503 (346)

Comparative reliability assessment of PET and UTCI thermal comfort indices using Monte Carlo simulation in urban microclimates. [PDF]

Sci Rep
Sargazi MA, Heidari A, Davtalab J, Piri J.   +3 more
europepmc   +1 more source

Computational methods for efficient nuclear data management in Monte Carlo neutron transport simulations

, 2014
Jonathan A. Walsh
openalex   +1 more source

Monte Carlo analysis of light fluence rate distribution in pleural photodynamic therapy: a study of geometric and optical property effects on treatment delivery. [PDF]

J Biomed Opt
Sun H, Johnson M, Sourvanos D, Zhu TC.
europepmc   +1 more source

Novel Approach to Uncertainty Study of Microseismic Hypocentres Using Bootstrap and Monte Carlo Methods in the Patuha Geothermal Field

Djoko A. Wibowo, Rendy Delliansyah, Chevy Iskandar, Istiawan Nurpratama   +3 more
openalex   +1 more source

Modeling Oxidative Stress-Linked Telogen Effluvium Using Monte Carlo Simulation of Published Trichoscopy Norms and Cannabis Exposure Distributions. [PDF]

Cureus
Chadha A, Burmeister M, Poelker-Wells S.
europepmc   +1 more source

Monte Carlo and Kinetic Monte Carlo Methods A Tutorial

, 2009
openaire   +2 more sources

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Monte Carlo Methods

GEM - International Journal on Geomathematics, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Michael P. Allen, Dominic J. Tildesley
semanticscholar   +6 more sources

Monte Carlo and quasi-Monte Carlo methods

Acta Numerica, 1998
Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N−1/2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction ...
R. Caflisch
openaire   +2 more sources

The Monte Carlo Method

Journal of the American Statistical Association, 1949
Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of Monte ...
N, METROPOLIS, S, ULAM
openaire   +2 more sources