摘要
概率逆换出现在通过专家判断进行模型参数的不确定风险分析中.由于缺乏基于相应判断的实验,专家往往不能直接评估参数的不确定性.本文对风险分析中的概率逆换算问题进行研究,并通过IPF算法和PARFUM算法得以实现.两种算法的可行性及迭代效果在实例中得到了验证和比较.不仅以数学的形式解决了概率逆换问题,而且使模型中的参数的不确定性得以量化.避免了专家主观估计法可能出现的偏见效应和权威效应.
Probabilistie inversion arises in risk and uncertainty analysis when uncertainty distributions over model parameters are obtained via expert judgment. Experts are often unable to assess their uncertainty on these parameters directly, as there are no corresponding experiments on which to base their judgments. This text researches the probabilistic inversion in risk a- nalysis, and gains implement using IPF and PARFUM algorithm, avoids the prejudice and princedom domino offect of expert subjective estimate by probabilistic inversion algorithm.
出处
《天津理工大学学报》
2008年第5期42-43,73,共3页
Journal of Tianjin University of Technology
基金
科技攻关计划重点科技攻关专项项目(05YFGZGX23700).