Results 21 to 30 of about 173,069 (310)

Modeling of lactose enzymatic hydrolysis using Monte Carlo method

open access: yesElectronic 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   +6 more
doaj   +1 more source

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

open access: yesJurnal 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   +2 more
doaj   +1 more source

Examining the Value of Monte Carlo Simulation for Project Time Management

open access: yesManagement, 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

Multilevel Monte Carlo methods [PDF]

open access: yesActa 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

open access: yesFrontiers 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   +1 more
doaj   +1 more source

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

open access: yesCommunications 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

Semistochastic Projector Monte Carlo Method

open access: yesPhysical Review Letters, 2012
We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix multiplication is partially implemented numerically exactly and partially with respect to expectation values only ...
Petruzielo, F. R.   +4 more
openaire   +5 more sources

Uma abordagem simplificada do método Monte Carlo Quântico: da solução de integrais ao problema da distribuição eletrônica A simplified approach to the Quantum Monte Carlo method: from the solution of integrals to the electronic distribution problem

open access: yesQuímica Nova, 2008
The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo ...
Wagner Fernando Delfino Angelotti   +3 more
doaj   +1 more source

Comparation of nonuniform and uniform Monte - Carlo Searching

open access: yesMATEC Web of Conferences, 2018
Nonuniform Monte-Carlo method is often used for optimization and solution of function mapping. This method has some disadvantages. New genetic algorithm, based on uniform Monte-Carlo is proposed by authors reduce disadvantage of nonuniform Monte- Carlo ...
Handrik Marián   +3 more
doaj   +1 more source

Optimized monte carlo methods [PDF]

open access: yes, 2008
I discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, like Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. I discuss reweighted data analysis and multi-hystogramming. I introduce Simulated Tempering, and as an example its application to the Random Field Ising Model.
openaire   +2 more sources

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