摘要
提出了一种基于云模型相似度的不确定知识排序方法,针对云模型表示的知识概念,基于云模型期望曲线在各维度的重叠度,计算概念彼此之间相似度,利用云模型相似度确定知识概念邻接云对,构造知识概念关系图,对使用云模型表示的知识概念进行排序,实现知识概念到语言变量值的映射.实验以二维数据为例,划分出多个知识概念,并用云模型表示,实验结果表明该方法能够有效地将知识概念同定性语言变量值进行对应.
This paper proposes a sorting method for uncertain knowledge based on cloud model similarity.First,for the knowledge concepts represented by the cloud model,the overlap of the expected curve of the cloud model in each dimension is used to calculate the similarity between concepts.Then,the concept adjacent cloud pair is constructed by using the similarity of cloud model.The knowledge concept map is further constructed to sort the knowledge concepts represented by the cloud model,and the mapping of knowledge concepts to the language variables is realized.Experiments on two-dimensional data were carried out to classify several knowledge concepts,which were represented by cloud model.The experimental results show that this method can effectively correspond the knowledge concepts to the qualitative language variables.
作者
李金武
LI Jinwu(College of Big Data and Artificial Intelligence,Zhengzhou University of Science&Technology,Zhengzhou 450064,China)
出处
《许昌学院学报》
CAS
2023年第5期113-119,共7页
Journal of Xuchang University
基金
河南省高等学校重点科研项目(23B520027)。
关键词
云模型
相似度
不确定知识
语言变量
排序
cloud model
similarity
uncertain knowledge
language variable
sort
