1) α-level optimization
α-截集优化
1.
In the case of both fuzzy and random parameters occur together,combining Monte Carlo random sampling of probability distribution functions with fuzzy possibility distribution of fuzzy parameter,the fuzzy result set was obtained by using-level optimization method with evolution strategy.
针对模糊参数和随机参数同时存在的情况,运用蒙特卡罗随机模拟产生随机样本,结合模糊可能性分布,通过使用进化策略的α-截集优化方法,进行模糊分析,从而获得模糊结果的集合。
2) α-cut
α-截集
1.
Rough approximations based on α-cut and strong β-cut of fuzzy set μ_X~R;
基于模糊集μ_X~R的α-截集和强β-截集的粗近似
2.
The importance of technical characteristics was calculated by fuzzy weighted average method based on α-cut.
应用基于α-截集的模糊加权平均方法求解技术特性的重要度。
3.
The definition of α-cut and Zadeh s extension principle are applied to transforming multiple-server fuzzy queues,of which the arrival rate and service rate are both fuzzy numbers,into conventional multiple-server queues.
应用α-截集的定义和Zadeh的扩展原理,将到达率和服务率均为模糊数的多列模糊排队问题转化为传统的多列排队问题。
5) a-strong level set
α-强截集
6) the combination of the random membership function
α-β截集
补充资料：下截
1.谓事物或人体的下半部分。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条