scholarly journals Simulation of Genetic Systems by Automatic Digital Computers

1958 ◽  
Vol 11 (4) ◽  
pp. 603 ◽  
Author(s):  
JSF Barker
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Stochastic Processes ◽  
Digital Computer ◽  
Gene Frequencies ◽  
New Approach ◽  
Electronic Digital Computer ◽  
Selection Processes ◽  
The Monte Carlo Method ◽  
Experimental Populations

A new approach to analysis of the effect of selection on gene frequencies is described. An electronic digital computer (the SILLIAC) is used to simulate the selection processes that operate in populations. The Monte Carlo method permits inclusion of stochastic processes so that results should simulate those in natural or experimental populations.

Independent and Dependent Scattering for Semitransparent Media Containing Bubbles

2004 ◽  
Author(s):  
Jaona H. Randrianalisoa ◽  
Dominique Baillis
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Bubble Size ◽  
Volume Fraction ◽  
Geometric Optic ◽  
New Approach ◽  
The Monte Carlo Method ◽  
Spherical Bubbles ◽  
Optic Limit ◽  
Radiative Characteristics

The objective of this present work is to provide a new approach for the radiative characteristics computation of semitransparent media containing spherical bubbles. The bubble size is considred much larger than the wavelength. First, previous models from the literature based on the independent theory are reviewed and established in the Geometric optic limit. Second, a predictive model using the Monte Carlo method is developed. The results obtained from the independent theory models and the Monte Carlo approach are compared. In addition, by varying the bubbles volume fraction, we investigate the limit of validity of the independent theory in such medium.

Paper 35: Some Aspects of Measurement of Roundness

1967 ◽  
Vol 182 (11) ◽  
pp. 425-429 ◽  
Author(s):  
A. N. Avdulov ◽  
Y. L. Polunov ◽  
A. N. Tabenkin ◽  
I. A. Faradjev ◽  
V. G. Shuster
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Digital Computer ◽  
Statistical Characteristics ◽  
The Monte Carlo Method

This paper deals with the analysis of the extent to which the results obtained from the measurements of the same graph may vary while using different reference circles. The statistical characteristics of the graph were obtained experimentally, and the algorithms for circles were worked out. The analysis was carried out by the Monte-Carlo method on a digital computer.

scholarly journals Monte Carlo Methods and the Koksma-Hlawka Inequality

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 725
Author(s):  
Sergey Ermakov ◽  
Svetlana Leora
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Processes ◽  
Random Numbers ◽  
Average Order ◽  
New Approach ◽  
Average Value ◽  
Acceptable Accuracy ◽  
Cubature Formulas ◽  
The Monte Carlo Method

The solution of a wide class of applied problems can be represented as an integral over the trajectories of a random process. The process is usually modeled with the Monte Carlo method and the integral is estimated as the average value of a certain function on the trajectories of this process. Solving this problem with acceptable accuracy usually requires modeling a very large number of trajectories; therefore development of methods to improve the accuracy of such algorithms is extremely important. The paper discusses Monte Carlo method modifications that use some classical results of the theory of cubature formulas (quasi-random methods). A new approach to the derivation of the well known Koksma-Hlawka inequality is pointed out. It is shown that for high ( s > 5 ) dimensions of the integral, the asymptotic decrease of the error comparable to the asymptotic behavior of the Monte Carlo method, can be achieved only for a very large number of nodes N. It is shown that a special criterion can serve as a correct characteristic of the error decrease (average order of the error decrease). Using this criterion, it is possible to analyze the error for reasonable values of N and to compare various quasi-random sequences. Several numerical examples are given. Obtained results make it possible to formulate recommendations on the correct use of the quasi-random numbers when calculating integrals over the trajectories of random processes.

Geometric Synthesis of Manipulators Using the Monte Carlo Method

1990 ◽  
Vol 112 (3) ◽  
pp. 450-452 ◽  
Author(s):  
J. Rastegar ◽  
B. Fardanesh
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Installation Space ◽  
Joint Motion ◽  
Task Space ◽  
Arbitrary Geometry ◽  
New Approach ◽  
Space Geometry ◽  
The Monte Carlo Method

A new approach to the solution of problems of geometric synthesis of manipulators is presented. It utilizes the Monte Carlo method, is general, and can be applied to any type of manipulator. Joint motion limitations can be included. The task space may have any arbitrary geometry. The allowable manipulator installation space is determined. Synthesis for a specified number of possible configurations (branches), and optimization of task space geometry are discussed.

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

PSHA software review based on the Monte Carlo method

2020 ◽  
pp. 14-24
Author(s):  
V.A. Mironov ◽  
S.A. Peretokin ◽  
K.V. Simonov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Seismic Hazard ◽  
Hazard Analysis ◽  
Software Review ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Test Calculation ◽  
Seismic Surveys ◽  
The Monte Carlo Method

The article is a continuation of the software research to perform probabilistic seismic hazard analysis (PSHA) as one of the main stages in engineering seismic surveys. The article provides an overview of modern software for PSHA based on the Monte Carlo method, describes in detail the work of foreign programs OpenQuake Engine and EqHaz. A test calculation of seismic hazard was carried out to compare the functionality of domestic and foreign software.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

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