摘要
针对管理决策领域中的等级分析问题,构建了面向语义可解释性的有序聚类方法。首先,在获得样本的优势度的基础上,结合模糊描述和K-modes聚类方法建立海员幸福感指数的有序聚类方法;然后,在公理模糊集框架下对有序聚类结果赋予相应的语义解释,以此形成一种从定量到定性的决策辅助方法;最后,以我国海员职业幸福感指数的9175份有效调查问卷为研究样本,通过所构建的有序聚类方法得到海员职业幸福感指数的等级划分及其相应的语义描述,并分析了影响海员职业幸福感指数的内在原因。分析表明,所提方法不仅可以产生满足用户指定约束的有序聚类结果,而且聚类结果具有可解释性、可理解性,同时具有良好的辅助决策的价值。
For solving grade analysis problems in the field of management decisions,an ordered clustering method for semantic interpretability was proposed.Firstly,based on obtaining the dominance degrees of the samples,the fuzzy description and K-modes clustering method were combined to establish an ordered clustering method of Chinese seafarers’vocational happiness indexes.Secondly,the corresponding semantic interpretation was assigned to the ordered clustering results under the framework of Axiomatic Fuzzy Set(AFS);thereby,forming a decision-making aid method for transforming the quantitative information into the qualitative description.Finally,taking the 9175 valid questionnaires of Chinese seafarers’vocational happiness indexes as the research samples,the constructed ordered clustering method was applied to obtain the grading results of the seafarers’vocational happiness indexes as well as their semantic interpretation,and the factors influencing seafarers’vocational happiness indexes were analyzed.The proposed method can produce ordered clustering results that satisfy user-specified constraints,and the results are interpretable,understandable,and have good value in assistant decision-making.
作者
高苏
鲍君忠
王昕
王利东
GAO Su;BAO Junzhong;WANG Xin;WANG Lidong(School of Science,Dalian Maritime University,Dalian Liaoning 116026,China;Navigation College,Dalian Maritime University,Dalian Liaoning 116026,China)
出处
《计算机应用》
CSCD
北大核心
2022年第2期457-462,共6页
journal of Computer Applications
基金
国家自然科学基金资助项目(61803065)。
关键词
有序聚类
海员幸福感
可解释性
语义描述
模糊描述
ordered clustering
seafarer vocational happiness
interpretability
semantic description
fuzzy description
