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Engineering - Computational Intelligence and Complexity | The Monte Carlo Simulation Method for System Reliability and Risk Analysis

The Monte Carlo Simulation Method for System Reliability and Risk Analysis

Zio, Enrico

2013, XIV, 198 p.

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  • Illustrates the Monte Carlo simulation method and its application to reliability and system engineering to give the readers the sound fundamentals of Monte Carlo sampling and simulation
  • Explains the merits of pursuing the application of Monte Carlo sampling and simulation methods when realistic modeling is required so that readers may exploit these in their own applications
  • Includes a range of simple academic examples in support to the explanation of the theoretical foundations as well as  case studies provide the practical value of the most advanced techniques so that the techniques are accessible

Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling.

 

Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques.

 

This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.

Content Level » Professional/practitioner

Keywords » Latin Hypercube Sampling - Monte Carlo Simulation Method - Series-parallel Discrete State Systems - System Reliability and Risk Analysis - The Cross Entropy Method

Related subjects » Computational Intelligence and Complexity - Computational Science & Engineering - Probability Theory and Stochastic Processes

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