Spatial Diffusion Processes 2: Numerical Analysis

1979 ◽  
Vol 11 (3) ◽  
pp. 335-347 ◽  
Author(s):  
M J Webber ◽  
A E Joseph
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Numerical Analysis ◽  
Diffusion Process ◽  
Diffusion Processes ◽  
Model Solution ◽  
Spatial Diffusion ◽  
System Of Cities ◽  
Reasonable Description ◽  
Parameter Values

An earlier paper (Webber and Joseph, 1978) proposed a model of the process whereby messages diffuse between a system of cities and provided a means of approximating the solution to that model if cities can ‘self-infect’ themselves with the message. This paper continues the analysis of this model by investigating the case in which a city cannot send the message to itself. The analysis is numerical, and an alternative to Monte Carlo simulation is used. The results indicate that the diffusion process described by the model is highly predictable if information on the accessibility of cities is available. A second part of the paper shows that the approximation used in the earlier paper provides a reasonable description of the model solution for at least some parameter values.

On the statistics of the linked stress release model

2001 ◽  
Vol 38 (A) ◽  
pp. 176-187 ◽  
Author(s):  
Mark Bebbington ◽  
David S. Harte
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Numerical Analysis ◽  
Large Scale ◽  
Point Processes ◽  
Information Criterion ◽  
Stress Release ◽  
Stress Release Model ◽  
Using Data ◽  
Release Model

The paper reviews the formulation of the linked stress release model for large scale seismicity together with aspects of its application. Using data from Taiwan for illustrative purposes, models can be selected and verified using tools that include Akaike's information criterion (AIC), numerical analysis, residual point processes and Monte Carlo simulation.

scholarly journals Monte Carlo Methods and New Jump Diffusion Processes and Their Application in Gold Price

2017 ◽  
Author(s):  
Kutluk Kağan Sümer
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Standard Deviation ◽  
Diffusion Process ◽  
Wiener Process ◽  
Mean Reversion ◽  
Jump Diffusion ◽  
Gold Market ◽  
Jump Diffusion Process ◽  
Standard Deviations

This study aimed to execute Monte Carlo simulation method with Wiener Process, Generalized Wiener Process, Mean Reversion Process and Mean Reversion Jump Diffusion Process and to compare them and then expended with the idea of how to include negative and positive news shocks in the gold market to the Monte Carlo simulation. By enhancing the determination of the 3 standard deviation shocks within the process of Classic Mean Jump Diffusion Process, an enchanted model for the 1,96 and 3 standard deviation shocks were being used and additionally positive and negative shocks were added to the system in a different way. This new Mean Reversion Jump Diffusion Process that have been developed by Sümer, executes Monte Carlo simulation regarding the gold market return with five random variables that are chosen from Poisson distribution and one random variable chosen from the normal distribution. Additionally, by accepting volatilities as outlies over the 1,96 and 3 standard deviations with the effect of the new and good news and the standard deviations on the traditional approximate return and the standard deviations (volatility) and the obtained new approximate return and the new standard deviation (volatility) and compares them with the Monte Carlo simulations.

Monte Carlo Simulation of Diffusion Processes in Three-Component Alloys

2019 ◽  
Vol 62 (4) ◽  
pp. 691-697
Author(s):  
A. R. Khalikov ◽  
E. A. Sharapov ◽  
E. A. Korznikova ◽  
A. I. Potekaev ◽  
M. D. Starostenkov ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Diffusion Processes

Monte Carlo Simulation of Diffusion Process on Quasi-Lattice

1992 ◽  
Vol 31 (Part 1, No. 5A) ◽  
pp. 1417-1423 ◽  
Author(s):  
Yasushi Sasajima ◽  
Kazuhiko Sakayori ◽  
Minoru Ichimura ◽  
Mamoru Imabayashi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Diffusion Process

Requirements Derivation for RoboCup Small Size League Robot

2020 ◽  
Author(s):  
Gabriel B. Farias ◽  
Marcos R. O. A. Máximo ◽  
Rubens J. M. Afonso
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Mobile Robot ◽  
Robot Soccer ◽  
Control Laws ◽  
And Control ◽  
Parameter Values ◽  
Parameters Of Interest

This work develops a method for deriving requirements for the goalkeeper of the robot soccer competition RoboCup Small Size League (SSL) using Monte Carlo simulation. Initially, an overview of the SSL competition is presented and related works are shown. Then, the parameters of interest are selected and the developed method is discussed. Afterwards, different models and control laws are designed to simulate the goal defense performance for different parameter values. Finally, the data generated is analyzed and a set of requirements for the mobile robot is selected. Lastly, the method utility is evaluated and possible extensions of this work are proposed.

scholarly journals Jump Adapted Scheme Of a Non Mark Dependent Jump Diffusion Process with Application to the Merton Jump Diffusion Model

2017 ◽  
Vol 5 (4) ◽  
pp. 80
Author(s):  
Renaud Fadonougbo ◽  
George O. Orwa
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Diffusion Process ◽  
Strong Convergence ◽  
General Result ◽  
Jump Diffusion ◽  
Discretization Scheme ◽  
Complete Proof ◽  
Jump Diffusion Process ◽  
Jump Diffusion Model

This paper provides a complete proof of the strong convergence of the Jump adapted discretization Scheme in the univariate and mark independent jump diffusion process case. We put in detail and clearly a known and general result for mark dependent jump diffusion process. A Monte-Carlo simulation is used as well to show numerical evidence.

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