DEVELOPMENT OF THE PREDICTION GRAPH METHOD UNDER INCOMPLETE AND INACCURATE EXPERT ESTIMATES

Yu. Ya. Samokhvalov

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DEVELOPMENT OF THE PREDICTION GRAPH METHOD UNDER INCOMPLETE AND INACCURATE EXPERT ESTIMATES

机译：专家估计不完整和不准确的预测图方法的发展

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摘要

The author considers the mechanisms to process fuzzy experts' estimates in forecasting the time and possible solutions of scientific problems. The distribution function of the runtime probability is proposed. This function allows constructing the continuous, integral distribution of a random variable on its total domain, based on the aggregate of discrete interval beta distributions. As the consistency measure of the fuzzy estimates, the coefficient of variation of the left- and right-hand boundaries of the time interval is used. Application of the Monte Carlo method to find the expected expenses for the problem solution is described.

机译：作者考虑了处理模糊专家的估计值的机制，以预测科学问题的时间和可能的解决方案。提出了运行时间概率的分布函数。此功能允许根据离散区间β分布的总和来构造随机变量在其总域上的连续积分分布。作为模糊估计的一致性度量，使用时间间隔左右边界的变化系数。描述了蒙特卡罗方法在寻找问题解决方案的预期支出中的应用。

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来源
《Cybernetics and Systems Analysis》 |2018年第1期|75-82|共8页
作者
Yu. Ya. Samokhvalov;
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作者单位

Taras Shevchenko National University of Kyiv, Kyiv, Ukraine;

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收录信息美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
prediction; prediction graph; goal attainment time; beta distribution; expertise; experts' estimates; fuzzy estimates; Monte Carlo method;

机译：预测;预测图目标达成时间;Beta分布;专业知识;专家的估计;模糊估计;蒙特卡洛法;

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DEVELOPMENT OF THE PREDICTION GRAPH METHOD UNDER INCOMPLETE AND INACCURATE EXPERT ESTIMATES

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