Сравнение методов

	Гибридный анализ надежности	Метод Монте-Карло
Область	Планирование эксперимента	Принятие решений
Семейство	Process / pipeline	MCDM
Год появления	1990s–2000s (consolidated formulation ~2000–2006)	1949
Автор метода	Xiaoping Du, Achintya Haldar, and others; synthesized across structural and mechanical engineering communities	Metropolis, N., Ulam, S.
Тип	Quantitative reliability / uncertainty analysis method	Robustness wrapper — Monte Carlo uncertainty propagation
Основополагающий источник	Du, X., Sudjianto, A., & Huang, B. (2006). Reliability-Based Design With the Mixture of Random and Interval Variables. Journal of Mechanical Design, 127(6), 1068–1076.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Другие названия	HRA, hybrid uncertainty reliability, combined reliability analysis, probabilistic-possibilistic reliability analysis	—
Связанные	4	0
Сводка	Hybrid Reliability Analysis (HRA) quantifies the probability that an engineering system will perform its intended function when uncertain inputs are of two fundamentally different kinds: aleatory uncertainties (natural randomness, modelled with probability distributions) and epistemic uncertainties (lack of knowledge, modelled with intervals or fuzzy sets). By treating both uncertainty types simultaneously rather than collapsing them into a single probabilistic framework, HRA produces more truthful reliability estimates in design, structural, and systems engineering problems.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.