Metode Monte Carlo: Perbedaan antara revisi
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k Bot: Perubahan kosmetika |
k Bot: Penggantian teks otomatis (-algoritma; +algoritme) |
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'''Metode Monte Carlo''' adalah [[
<!--They are distinguished from other simulation methods (such as [[molecular dynamics]]) by being [[stochastic]], that is [[nondeterministic]] in some manner - usually by using [[random number]]s (or more often [[pseudo-random number]]s) - as opposed to [[deterministic algorithm]]s. -->
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<!--Interestingly, the Monte Carlo method does not require truly random numbers to be useful. Much of the most useful techniques use deterministic, pseudo-random sequences, making it easy to test and re-run simulations. The only quality usually necessary to make good [[simulation]]s is for the pseudo-random sequence to appear "random enough" in a certain sense. That is that they must either be [[uniform distribution|uniformly distributed]] or follow another desired distribution when a large enough number of elements of the sequence are considered.-->
Karena
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== Sejarah ==
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* Harvey Gould & Jan Tobochnik, ''An Introduction to Computer Simulation Methods, Part 2, Applications to Physical Systems'', [[1988]], ISBN 0-201-16504-X
* C.P. Robert and G. Casella. "Monte Carlo Statistical Methods" (second edition). New York: Springer-Verlag, [[2004]], ISBN 0-387-21239-6
* Pembuat paket komersial yang mengimplementasikan
* Mosegaard, Klaus., and Tarantola, Albert, 1995. Monte Carlo sampling of solutions to inverse problems. J. Geophys. Res., 100, B7, 12431-12447.
* Tarantola, Albert, ''Inverse Problem Theory'' ([http://www.ipgp.jussieu.fr/~tarantola/Files/Professional/SIAM/index.html versi PDF bebas]), Society for Industrial and Applied Mathematics, 2005. ISBN 0-89871-572-5
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