Results 21 to 30 of about 857,070 (293)

The Monte Carlo Method [PDF]

International Astronomical Union Colloquium, 1971
AbstractWe give here a detailed technical description of a Monte Carlo scheme for the dynamical evolution of spherical stellar systems. The philosophy of the method, as well as a few illustrative results, are given elsewhere (Hénon, 1971, hereafter called I).
openaire   +1 more source

Modeling of lactose enzymatic hydrolysis using Monte Carlo method

Electronic Journal of Biotechnology, 2019
Background: Mathematical modeling is useful in the analysis, prediction, and optimization of an enzymatic process. Unlike the conventional modeling methods, Monte Carlo method has special advantages in providing representations of the molecule’s spatial ...
Ling Gao, Qingqing Guo, Huibin Lin, Deng Pan, Xiaodong Huang, Jianqun Lin, Jianqiang Lin   +6 more
doaj   +1 more source

Error in Monte Carlo, quasi-error in Quasi-Monte Carlo [PDF]

, 2005
While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error.
Achilleas Lazopoulos, Adams, Bratley, Halton, Hoogland, Hoogland, James, James, Luescher, Niederreiter, Owen, Ronald Kleiss, Schlier, Weyl   +13 more
core   +2 more sources

The Coupled Electronic-Ionic Monte Carlo Simulation Method [PDF]

, 2002
Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies.
B. L. Hammond Jr., B. Militzer, B. Militzer, C. Lin, C. Pierleoni, D. Hohl, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. Marx, D. Saumon, D. Saumon, D. Saumon, I. F. Silvera, J. C. Grossman, J. Kohanoff, J. Kohanoff, M. C. Payne, M. Dewing, M. E. Tuckerman, M. Sprik, N. C. Holmes, N. Metropolis, P. Diep, P. Diep, P. J. Reynolds, R. Car, V. Natoli, V. Natoli, W. J. Nellis, W. M. C. Foulkes, Y. Kwon, Y. Kwon   +35 more
core   +2 more sources

Examining the Value of Monte Carlo Simulation for Project Time Management

Management, 2019
Research Question: This paper investigates whether the Monte Carlo simulation can be widely used as a practicable method for the analysis of the risks that impact project duration.
Goran Avlijas
doaj   +1 more source

ANALISIS PENGENDALIAN PERSEDIAAN BAHAN BAKU TANDAN BUAH SEGAR (TBS) DENGAN METODE SIMULASI MONTE CARLO

Jurnal Lebesgue, 2023
The development of palm oil production is quite rapid in Indonesia. The method used to estimate inventory costs in this study is the Monte Carlo Simulation method. Monte Carlo simulation is used in structuring optimal raw material policies.
Cindy Artika, Sajaratud Dur, Ismail Husein   +2 more
doaj   +1 more source

Benchmark of a new multi-ion-species collision operator for $\delta f$ Monte Carlo neoclassical simulation [PDF]

, 2020
A numerical method to implement a linearized Coulomb collision operator in the two-weight $\delta f$ Monte Carlo method for multi-ion-species neoclassical transport simulation is developed.
122862, 123636, 126346, 126422, 67562, 67563, 67564, 67588, Ishiguro, Seiji, KANNO, Ryutaro, MATSUOKA, Seikichi, Nakata, Motoki, NUNAMI, Masanori, Pianpanit, Theerasarn, SATAKE, Shinsuke, SUGAMA, Hideo   +15 more
core   +3 more sources

Multilevel Monte Carlo methods [PDF]

Acta Numerica, 2013
Monte Carlo methods are a very general and useful approach for the estimation of expectations arising from stochastic simulation. However, they can be computationally expensive, particularly when the cost of generating individual stochastic samples is very high, as in the case of stochastic PDEs.
openaire   +3 more sources

A Machine Learning Based Hybrid Multi-Fidelity Multi-Level Monte Carlo Method for Uncertainty Quantification

Frontiers in Environmental Science, 2019
This paper focuses on reducing the computational cost of the Monte Carlo method for uncertainty propagation. Recently, Multi-Fidelity Monte Carlo (MFMC) method (Ng, 2013; Peherstorfer et al., 2016) and Multi-Level Monte Carlo (MLMC) method (Müller et al.,
Nagoor Kani Jabarullah Khan, Ahmed H. Elsheikh   +1 more
doaj   +1 more source

Monte Carlo and Quasi Monte Carlo Approach to Ulam's Method for Position Dependent Random Maps

Communications in Advanced Mathematical Sciences, 2020
We consider position random maps $T=\{\tau_1(x),\tau_2(x),\ldots, \tau_K(x); p_1(x),p_2(x),\ldots,p_K(x)\}$ on $I=[0, 1],$ where $\tau_k, k=1, 2, \dots, K$ is non-singular map on $[0,1]$ into $[0, 1]$ and $\{p_1(x),p_2(x),\ldots,p_K(x)\}$ is a set of
Md Shafiqul Islam
doaj   +1 more source