Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications

@article{Kreinovich2007MonteCarloTypeTF,
  title={Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications},
  author={Vladik Kreinovich and Jan Beck and Carlos Ferregut and Araceli S{\'a}nchez and G. Randy Keller and Matthew G. Averill and Scott A. Starks},
  journal={Reliable Computing},
  year={2007},
  volume={13},
  pages={25-69}
}
In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the probability distribution of different uncertain parameters. Usually, we can safely linearize the dependence of the desired quantities y (e.g., stress at different structural points) on the uncertain parameters xi – thus enabling sensitivity analysis. Often, the number n of uncertain parameters is huge, so sensitivity analysis… CONTINUE READING

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