Simulation & Optimization Methods in Risk & Reliability Theory

This book introduces recent advances in the area of risk estimation in complex systems.

The authors study new methods of accelerated modelling, asymptotical analysis and optimal estimating.

The processes are modelled using large failure trees, the methodology of fuzzy sets, bayesians, methods of stochastic optimisation, and optimal models of equipment service and control.

The authors suggest applying numerical methods for analysis of super-large failure trees having large amount of multiple vertices.

The methods allow finding minimal sections and reducing the amount of time necessary for such calculations.

The Bayesians theory is applied under conditions of uncertainty.

The methods of finding robust parameter estimates for the most commonly used classes of a priori distribution functions are suggested.

As an alternative approach to stochastic methods the authors propose the algorithums of critical stats estimation for the reactor's active zone that utilise the theory of fuzzy logic.