统一
计算机科学
背景(考古学)
群体决策
转化(遗传学)
灵活性(工程)
信息融合
基于规则的机器翻译
偏爱
语言学
自然语言处理
人工智能
数学
统计
心理学
程序设计语言
社会心理学
生物
生物化学
基因
哲学
古生物学
化学
作者
Yuzhu Wu,Yuan Gao,Bowen Zhang,Witold Pedrycz
标识
DOI:10.1016/j.inffus.2022.07.009
摘要
In the problems that linguistic assessments are conducted by adopting multiple sources of information representations, the management of unification of heterogeneous information and information loss are necessary. To support a useful fusion of heterogeneous distributed information in linguistic group decision making, a minimum information-loss transformation framework is proposed in this paper. First, distributed linguistic distance measurements are defined to measure information loss among heterogeneous distributed linguistic preference information, and then several minimum information-loss transformation models (MILTMs) with desirable properties are proposed. Furthermore, the application of the MILTMs in addressing the fusion of heterogeneous distributed linguistic information in a multi-attribute group decision context is discussed, and the flexibility of distributed linguistic information is studied to justify the MILTMs through numerical examples and comparative analyses.
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