计算机科学
粗集
模棱两可
模糊集
人工智能
决策工程
集合(抽象数据类型)
期限(时间)
证据推理法
决策论
商业决策图
决策分析
决策支持系统
模糊逻辑
数学
数理经济学
物理
统计
量子力学
程序设计语言
出处
期刊:Journal of Intelligent and Fuzzy Systems
[IOS Press]
日期:2023-07-02
卷期号:45 (1): 285-304
被引量:2
摘要
The three-way decision model based on linguistic term sets has been extensively investigated since decision makers frequently utilize natural language to evaluate in an actual decision-making process. The existing models require decision makers to select appropriate linguistic terms from a given linguistic term set. However, making such a choice is not always simple, and decision makers occasionally choose words that are related to their own experience. In order to deal with this kind of decision problem, we appeal to the theory of computing with words pioneered by Zadeh and establish a three-way decision model based on computing with words in this paper. The paper focuses on how to deal with more general linguistic information using the theory of computing with words. Initially, using the concept of computing with words, we translate more broad linguistic information into a linguistic distribution assessment on a balanced linguistic term set in order to better analyze linguistic information. The three-way decision based on computing with words is then discussed. Decision-theoretic rough fuzzy sets take into account the ambiguity of the decision target as a generalization of the classical decision-theoretic rough sets. This is what motivated us to develop a three-way decision based on decision-theoretic rough fuzzy sets using computing with words. Additionally, a fabricated example demonstrates that our three-way decision model is more adaptable in processing linguistic information and can handle more general linguistic information provided by decision makers.
科研通智能强力驱动
Strongly Powered by AbleSci AI