基于调和概率语言术语集的Power平均算子

Power Averaging Operator Based on the Adjusted Rules of Probabilistic Linguistic Term Sets

实践发现现存概率语言Power平均算子在应用中存在概率信息丢失、计算过于繁琐等问题,针对这些问题,提出一种基于调和概率语言术语集的Power平均算子。结合新的基本运算法则与新的支撑度,给出新的概率语言Power平均算子、概率语言Power几何平均算子、概率语言Power加权平均算子、概率语言Power加权几何平均算子,同时论证分析了这几类新型算子的性质。最后通过实验数据,将提出的算子与现存算子进行对比分析,验证了所提算子的有效性与可行性。

In practical applications,it has been observed that the existing probabilistic linguistic power averaging operator faces challenges such as loss of probability information and overly complex calculations.To address these issues,this paper proposes a power averaging operator based on adjusted probabilistic linguistic term sets.By combining new basic operational rules with a new support degree,this study introduces new probabilistic linguistic power averaging operator,probabilistic linguistic power geometric operator,weighted probabilistic linguistic power averaging operator,and weighted probabilistic linguistic power geometric operator.At the same time,the properties of these new types of operators are demonstrated and analyzed.Finally,experimental data is utilized to compare and analyze the proposed operators against existing operators,thereby verifying the effectiveness and feasibility of the proposed operators.