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Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results.
This book provides a comprehensive overview of these methods, discussing their fundamental aspects and their applications in solving a large array of problems. It is a useful reference for scholars, researchers, and students in pure and applied mathematics, physical sciences, engineering and technology, computer science, numerical analysis, scientific computing, and the general sciences.
Lanchester’s Fighting Strength as a Battle Outcome Predictor Applied to a Simple Fire and Manoeuvre Wargame
A New Monte Carlo Approach for the Solution of Semi-Linear Neumann Boundary Value Problem
The Effect of Anode, Hot and Cold Cathode Structures Used in Miniature X-Ray Tubes on X-Ray Output Using Monte Carlo Simulation
Random Sampling-and-Averaging with Variance-Reduction Techniques in Quantum Measurements
Path Integrals and Smart Monte Carlo – I