属性权重未知的不确定语言评价双边匹配决策

Uncertain Bilaterally Matching Decision-making with Uncertain Weights

针对匹配主体没有提供属性权重信息的不确定多粒度语言评价双边匹配问题,提出了一种基于离差最大公式和二元语义的决策方法。决策中,首先创建一个基本语言评价集(BLTS),将多粒度的不确定语言评价信息转换为区间二元语义,并且将所有区间二元语义根据公式投影到基本语言评价集上。根据区间二元语义的距离公式,计算属性之间的离差。通过离差最大化公式,计算得到每个匹配主体的属性权重向量。进而通过属性权重对区间二元语义加权平均,根据理想逼近法计算最终的满意度,得到最终的求解模型。最后通过实验证明该决策方法的可行性。

A decision method based on the maximum formula of deviation and two-tuple semantics is proposed to evaluate the bilateral matching problem of uncertain multi-granularity language evaluation with no weight information provided by the matching subject.In the decision,a basic language evaluation set(BLTS)is first created,which converts the multi-granularity uncertain language evaluation information to the interval two element semantics,and all the interval two-tuple semantics are projected to the basic language evaluation set.Then,according to the distance formula of interval two-tuple linguistic,the deviation between attributes is calculated.The weight vector of each matching body is calculated through the maximum deviation formula.Then,by weighting the interval binary semantic formaldehyde average,the final satisfaction is calculated according to the ideal approximation method,and the final solution model is obtained.Finally,the feasibility of the decision-making method is proved by experiments.