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The Monte Carlo Simulation Method for System Reliability and Risk Analysis

assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates;

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Engineering Risk Assessment with Subset Simulation

simulation. * Presents a powerful simulation method called Subset Simulation for efficient engineering risk assessment and failure and sensitivity;

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Project Valuation and Decision Making under Risk and Uncertainty applying Decision Tree Analysis and Monte Carlo Simulation

Monte Carlo Simulation technique and the Decision Tree Analysis approach to form a comprehensive method for project valuation under risk and;

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Simulation and the Monte Carlo Method

sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and;

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Computational Methods For Reliability And Risk Analysis

. In particular, it provides: i) a basic illustration of some methods used in reliability and risk analysis for modelling the stochastic failure and;

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Monte Carlo Methods in Finance

dynamics, simulation is the only method general enough to capture the complexity and Monte Carlo simulation is the best pricing and risk management;

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Student Solutions Manual To Accompany Simulation And The Monte Carlo Method

for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross;

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New Computational Methods in Power System Reliability

simulation and with random processes methods, Semi-Markov and Markov reward models and genetic algorithm. The book can be considered as complementary;

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New Computational Methods in Power System Reliability

simulation and with random processes methods, Semi-Markov and Markov reward models and genetic algorithm. The book can be considered as complementary;

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A Primer for the Monte Carlo Method

Primer for the Monte Carlo Method demonstrates how practical problems in science, industry, and trade can be solved using this method. The book;

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A Primer for the Monte Carlo Method

Primer for the Monte Carlo Method demonstrates how practical problems in science, industry, and trade can be solved using this method. The book;

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Handbook in Monte Carlo Simulation

and risk management to optimization. The Handbook in Monte Carlo Simulation features: * An introductory section for basic material on;

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Monte-carlo Methods and Stochastic Processes

basic tools for stochastic simulation and analysis of algorithm convergence. The second part describes Monte-Carlo methods for the simulation;

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Monte-Carlo Methods and Stochastic Processes

basic tools for stochastic simulation and analysis of algorithm convergence. The second part describes Monte-Carlo methods for the simulation;

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Handbook of Monte Carlo Methods

* Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation;

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Reliability and Risk Models

reliability networks for engineering systems. Includes: * A unique set of 46 generic principles for reducing technical risk * Monte Carlo simulation;

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Telecommunications System Reliability Engineering, Theory, and Practice

prediction in telecommunications systems. Bringing the field of telecommunications system reliability analysis up to date, this textbook provides;

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Risk Analysis

. Quantitative risk analysis (QRA) using Monte Carlo simulation offers a powerful and precise method for dealing with the uncertainty and variability;

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Reliability and Safety Engineering

applications with state-of-the-art methods used in reliability and risk assessment of engineering systems. It is designed to assist practicing;

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Monte Carlo Methods and Models in Finance and Insurance

focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation;

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Quantum Monte Carlo Methods

methods for computing ground and excited states, and the variational Monte Carlo method. Also discussed are continuous-time algorithms for quantum;

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Monte Carlo Applications In Systems Engineering

source for a comprehensive description of the utilization of Monte Carlo methods in practical engineering problems. The author suggests that;

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Monte Carlo Methods

discusses the Monte Carlo methods needed for the estimation of the mean glandular dose in both digital mammography and digital breast tomosynthesis;

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Mean Field Simulation for Monte Carlo Integration

. Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle;

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Mean Field Simulation for Monte Carlo Integration

. Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle;

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Probability, Statistics, and Reliability for Engineers and Scientists

and Scientists, Third Edition introduces the fundamentals of probability, statistics, reliability, and risk methods to engineers and;

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Modern Risk Quantification in Complex Projects

risk quantification methodology in complex projects. Results produced by the system dynamics and the non-linear Monte Carlo methodologies are;

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