提出高效生成带区间核的LR模糊数的模拟算法
Simulation of Random LR Fuzzy Intervals
- 基于分段线性LR模糊数的区间核结构设计模拟方法
- 推导出该类模糊数的极限行为以优化算法效率
- 适合需要随机模糊数据生成的研究者使用
随机模糊变量结合了模糊性（源于其‘模糊部分’）与随机性，其统计样本被广泛应用，因此需要直接且数值高效的生成方法。通常样本由三角或梯形模糊数构成。本文描述了另一类模糊数——具有区间值核的LR模糊数的理论结果与模拟算法。从分段线性LR模糊数带区间核的模拟视角出发，研究其极限行为，进而提出一种高效数值算法，用于生成此类模糊值的样本。
原文摘要 · Abstract (English)
Random fuzzy variables join the modeling of the impreciseness (due to their ``fuzzy part'') and randomness. Statistical samples of such objects are widely used, and their direct, numerically effective generation is therefore necessary. Usually, these samples consist of triangular or trapezoidal fuzzy numbers. In this paper, we describe theoretical results and simulation algorithms for another family of fuzzy numbers -- LR fuzzy numbers with interval-valued cores. Starting from a simulation perspective on the piecewise linear LR fuzzy numbers with the interval-valued cores, their limiting behavior is then considered. This leads us to the numerically efficient algorithm for simulating a sample consisting of such fuzzy values.
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