Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~^), 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 techniques. Accelerated convergence for Monte Ca...

This paper surveys recent research on using Monte Carlo techniques to improve quasi-Monte Carlo techniques. Randomized quasi-Monte Carlo methods provide a basis for error estimation. They have, in the special case of scrambled nets, also been observed to improve accuracy. Finally through Latin supercube sampling it is possible to use Monte Carlo methods to extend quasi-Monte Carlo methods to hi...

monte carlo simulation is a standard technique for project risk analysis. however, some assumptions of this technique are not reasonable in real world. when a project falls behind the schedule, managers take actions to improve the performance. nevertheless, most of the simulation models as monte carlo omit these reactions in their analysis, which results in unreasonable wide distributions or ev...

the hydration of biomolecules is vitally important in molecular biology, so in this paper thesolvation energy and radial distribution function of dna bases have been calculated by themonte carlo simulation.the geometries of isolated adenine, guanine, cytosine, and thyminehave been optimized using 6-31+g(d,p) basis function sets. these geometries then will be used inthe monte carlo calculation o...

Background: Monte Carlo (MC) modeling of a linear accelerator is a prerequisite for Monte Carlo dose calculations in external beam radiotherapy. In this study, a simple and efficient model was developed for Elekta SL-25 linear accelerator using MCNP4C Monte Carlo code Materials and methods: The head of Elekta SL-25 linac was simulated for 6 and 18 MV photon beams using MCNP4C MC code. Energ...