基于犹豫语言算法的网络舆情预测模型选择

Selection of Network Public Opinion Prediction Model Based on the Hesitant Linguistic Aggregation Algorithm

对于属性评估信息伟犹豫模糊语言变量的多准则决策问题,同时考虑输入数据之间具有一定关系,设计了一种基于犹豫模糊语言B-平均（HFLBM）信息集成算法的决策模型。利用定义在犹豫模糊语言元（HFLE）上的Archimedean基本运算法则,首先设计了新的HFLBM信息集成算法;然后,详细探讨了提出的算法的四种优良性质和它的比较常用形式,并考虑到HFLE的重要性不同定义了它的加权形式,即犹豫模糊语言加权Bonferroni（HFLWBM）信息集成算法;最后,在犹豫模糊语言信息环境下,运用HFLWBM信息集成算法提出一种网络舆情预测模型选择方法,实验表明提出的决策模型是可行的和有效的。

In the hesitant fuzzy linguistic information environment, for the multi-criteria decision making（MCDM） problem that there is a relationship between input variables, a decision-making model is investigated on the basis of the hesitant fuzzy linguistic B-mean（HFLBM） information integration algorithm. By using the basic Archimedean algorithm, which is defined on the hesitant fuzzy linguistic element（HFLE）, the HFLBM information integration algorithm is first designed. Secondly, the four excellent properties of the proposed algorithm and its common forms are discussed in detail, and the hesitant fuzzy linguistic weighted B-mean（HFLWBM） information integration algorithm is defined by considering the different importance of HFLE. Finally, in the hesitant fuzzy linguistic information environment, a selection method of the network public opinion prediction model is proposed by using the HFLWBM information integration algorithm, and the experiment shows that the proposed decision-making model is feasible and effective.