Simplified Approach to Identifying Influential Uncertainties in Monte Carlo Analysis

Toshikazu Motoda

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Simplified Approach to Identifying Influential Uncertainties in Monte Carlo Analysis

机译：蒙特卡洛分析中确定影响不确定性的简化方法

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A simplified approach of identifying influential uncertain parameters in Monte Carlo analysis was presented, and its validity was investigated. Because computational inconvenience is avoided, the simplified test can be easily applied even when a large number of simulations is required for the identification. The accuracy of the simplified test was investigated, and the validity of the simplified approach was demonstrated in an example. The simplified test is found to be practically efficient, and by its application, Monte Carlo simulation will become a still more efficient tool for system evaluation in the development of flight vehicles.

机译：提出了一种在蒙特卡洛分析中确定影响不确定性参数的简化方法，并对其有效性进行了研究。因为避免了计算上的不便，所以即使需要大量的模拟来进行识别，也可以轻松地应用简化的测试。研究了简化测试的准确性，并在一个示例中证明了简化方法的有效性。发现简化的测试实际上是有效的，并且通过其应用，蒙特卡洛模拟将成为飞行器开发中用于系统评估的更加有效的工具。

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来源
《Journal of Spacecraft and Rockets》 |2004年第6期|p.1071-1075|共5页
作者
Toshikazu Motoda;
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作者单位

Japan Aerospace Exploration Agency, Tokyo 181-0015, Japan;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类航空;
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专利

1. Identification Influential Uncertainties in Monte Carlo Analysis [J] . Toshikazu Motoda, Yoshikazu Miyazawa Journal of Spacecraft and Rockets . 2002,第4期

机译：蒙特卡洛分析中的识别影响不确定性
2. Identifying influential observations in Bayesian models by using Markov chain Monte Carlo [J] . JacksonD., WhiteI.R., CarpenterJ. Statistics in medicine . 2012,第11a12期

机译：使用马尔可夫链蒙特卡罗识别贝叶斯模型中的影响性观察
3. Monte Carlo vs. Fuzzy Monte Carlo Simulation for Uncertainty and Global Sensitivity Analysis [J] . Young-Jin Kim Sustainability . 2017,第4期

机译：不确定性和全局敏感性分析的蒙特卡洛与模糊蒙特卡洛模拟
4. Brief overview of methods for measurement uncertainty analysis: GUM uncertainty framework, Monte Carlo method, characteristic function approach [C] . V. Witkovský, G. Wimmer, Z. Ďurišová, 11th International Conference on Measurement . 2017

机译：测量不确定度分析方法的简要概述：GUM不确定度框架，蒙特卡洛方法，特征函数方法
5. A Bayesian Markov Chain Monte Carlo Approach to Uncertainty Quantification [D] . Isaac, Matthew. 2020

机译：贝叶斯马尔可夫链蒙特卡罗的不确定量化方法
6. Identifying influential observations in Bayesian models by using Markov chain Monte Carlo [O] . Dan Jackson, Ian R White, James Carpenter -1

机译：使用马尔可夫链蒙特卡罗识别贝叶斯模型中的影响性观察
7. A Simplified Approach To The Quantum Monte Carlo Method: From The Solution Of Integrals To The Electronic Distribution Problem [uma Abordagem Simplificada Do Método Monte Carlo Quântico: Da Solução De Integrais Ao Problema Da Distribuição Eletrônica] [O] . Angelotti W.F.D., Da Fonseca A.L., Torres G.B., 2015

机译：量子蒙特卡洛方法的一种简化方法：从积分的解到电子分布问题

Simplified Approach to Identifying Influential Uncertainties in Monte Carlo Analysis

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