Monte Carlo Study of Polymer Systems by Multiple Markov Chain Method

1998 ◽  
pp. 33-57 ◽  
Author(s):  
Enzo Orlandini
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Monte Carlo Study ◽  
Polymer Systems ◽  
Markov Chain Method

Sparse Code Multiple Access Decoding Based on a Monte Carlo Markov Chain Method

2016 ◽  
Vol 23 (5) ◽  
pp. 639-643 ◽  
Author(s):  
Jienan Chen ◽  
Zhenbing Zhang ◽  
Shuaining He ◽  
Jianhao Hu ◽  
Gerald E. Sobelman
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Multiple Access ◽  
Monte Carlo Markov Chain ◽  
Sparse Code ◽  
Markov Chain Method

A Bayesian Monte Carlo Markov Chain Method for Loss Models and Risk Measure Assessments

2009 ◽  
Vol 12 (03) ◽  
pp. 529-543
Author(s):  
Ling Hu ◽  
Yating Yang
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Normal Distribution ◽  
Risk Measure ◽  
Markov Chain Method ◽  
Flood Loss ◽  
Bayesian Monte Carlo ◽  
Loss Models ◽  
Log Normal ◽  
Log Normal Distribution

Natural disasters are also known as catastrophes with low frequency but high damages. Typhoons and floods are the major catastrophes which lead to gargantuan losses in Asia. Once a disaster occurs, a broad region will be affected and this will result in huge social loss. If issuers or governments use the wrong loss models or risk measure indexes to price the related insurance products, they will get an inaccurate price and thus be insolvent to the claims. Previous researches often use a Log-Normal distribution to model a catastrophic loss. This is not appropriate since the characteristics of a loss distribution have some empirical facts, including the positive skewness and the heavy-tailed properties. Recently, some studies (McNeil and Frey, 2000; Rootzen and Tajvidi, 2000; Thuring et al., 2008) also point out that using Log-Normal distribution to model a characteristic loss is not suitable. Therefore, we build a typhoon and flood loss model with higher order moments and estimate the parameters through a Bayesian Monte Carlo Markov Chain method. According to the Kolmogorov-Smirnov test, we find that the Pareto distribution is more adaptive for modeling the loss of typhoon and flood. Further, we evaluate different kinds of risk measure indexes through simulating and numerical analysis. It gives the beacon to issuers or governments when they want to issue the insurance products about typhoon and flood loss.

Streamline-Based History Matching and Uncertainty--Markov-Chain Monte Carlo Study of an Offshore Turbidite Oil Field

2007 ◽  
Author(s):  
Marko Maucec ◽  
Sippe G. Douma ◽  
Detlef Hohl ◽  
Jaap Leguijt ◽  
Eduardo Jimenez ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
History Matching ◽  
Monte Carlo Study ◽  
Oil Field

scholarly journals Markov Chain Investigation of Discretization Schemes and Computational Cost Reduction in Modeling Photon Multiple Scattering

2018 ◽  
Vol 8 (11) ◽  
pp. 2288 ◽  
Author(s):  
Shangze Yang ◽  
Di Xiao ◽  
Xuesong Li ◽  
Zhen Ma
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Multiple Scattering ◽  
Cost Reduction ◽  
Computational Cost ◽  
Detailed Comparison ◽  
Iterative Approach ◽  
Computational Costs ◽  
Markov Chain Method ◽  
Discretization Schemes

Establishing fast and reversible photon multiple scattering algorithms remains a modeling challenge for optical diagnostics and noise reduction purposes, especially when the scattering happens within the intermediate scattering regime. Previous work has proposed and verified a Markov chain approach for modeling photon multiple scattering phenomena through turbid slabs. The fidelity of the Markov chain method has been verified through detailed comparison with Monte Carlo models. However, further improvement to the Markov chain method is still required to improve its performance in studying multiple scattering. The present research discussed the efficacy of non-uniform discretization schemes and analyzed errors induced by different schemes. The current work also proposed an iterative approach as an alternative to directly carrying out matrix inversion manipulations, which would significantly reduce the computational costs. The benefits of utilizing non-uniform discretization schemes and the iterative approach were confirmed and verified by comparing the results to a Monte Carlo simulation.

Uniaxial deformation of bridging polymer systems: A Monte Carlo study

1997 ◽  
Vol 106 (18) ◽  
pp. 7792-7801 ◽  
Author(s):  
Th. Hölzl ◽  
M. Wittkop ◽  
S. Kreitmeier ◽  
D. Göritz
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Uniaxial Deformation ◽  
Polymer Systems
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