Theory and Applications of Monte Carlo Simulations

Victor (Wai Kin) Chan

• Publisher: IntechOpen
• Year: 2013
• Print ISBN:
  9789535110125
• eBook ISBN:
  9789535157243
• Topic: Ciencia de la computación
• Subtopic: Algoritmos de programación

The purpose of this book is to introduce researchers and practitioners to recent advances and applications of Monte Carlo Simulation (MCS). Random sampling is the key of the MCS technique. The 11 chapters of this book collectively illustrates how such a sampling technique is exploited to solve difficult problems or analyze complex systems in various engineering and science domains. Issues related to the use of MCS including goodness-of-fit, uncertainty evaluation, variance reduction, optimization, and statistical estimation are discussed and examples of solutions are given. Novel applications of MCS are demonstrated in financial systems modeling, estimation of transition behavior of organic molecules, chemical reaction, particle diffusion, kinetic simulation of biophysics and biological data, and healthcare practices. To enlarge the accessibility of this book, both field-specific background materials and field-specific usages of MCS are introduced in most chapters. The aim of this book is to unify knowledge of MCS from different fields to facilitate research and new applications of MCS.

Table of contents

• Theory and Applications of Monte Carlo Simulations
• Contents
• Preface
• Chapter 1 Monte Carlo Statistical Tests for Identity of Theoretical and Empirical Distributions of Experimental Data
• Chapter 2 Monte Carlo Simulations Applied to Uncertainty in Measurement
• Chapter 3 Fractional Brownian Motions in Financial Models and Their Monte Carlo Simulation
• Chapter 4 Monte-Carlo-Based Robust Procedure for Dynamic Line Layout Problems
• Chapter 5 Comparative Study of Various Self-Consistent Event Biasing Schemes for Monte Carlo Simulations of Nanoscale MOSFETs
• Chapter 6 Atomistic Monte Carlo Simulations on the Formation of Carbonaceous Mesophase in Large Ensembles of Polyaromatic Hydrocarbons
• Chapter 7 Variance Reduction of Monte Carlo Simulation in Nuclear Engineering Field
• Chapter 8 Stochastic Models of Physicochemical Processes in Catalytic Reactions - Self-Oscillations and Chemical Waves in CO Oxidation Reaction
• Chapter 9 Monte-Carlo Simulation of Particle Diffusion in Various Geometries and Application to Chemistry and Biology
• Chapter 10 Kinetic Monte Carlo Simulation in Biophysics and Systems Biology
• Chapter 11 Detection of Breast Cancer Lumps Using Scattered X-Ray Profiles: A Monte Carlo Simulation Study