无序样品聚类分析——综合评分法
Cluster analysis of disordered samples: comprehensive scoring method
投稿时间:2024-06-03  修订日期:2024-06-03
DOI:
中文关键词:  无序样品  有序样品  高优指标  低优指标  聚类分析  综合评价
英文关键词:Disordered samples  Ordered samples  High superiority indicators  Low superiority indicators  Cluster analysis  Comprehensive evaluation
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作者单位地址
胡纯严 军事科学院研究生院 北京海淀厢红旗东门外甲1号
胡良平* 军事科学院研究生院 北京海淀厢红旗东门外甲1号
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中文摘要:
      本文目的是介绍与无序样品聚类分析有关的基本概念、计算方法、两个实例及使用SAS实现计算的方法。基本概念包括无序样品与有序样品、聚类分析与综合评价、高优指标、低优指标和望目指标、排序与分档、标准化变换;计算方法涉及基于专家评分的综合评分法计算公式以及基于变量观测值的综合评分法计算公式;两个实例分别为“1982年我国16个地区农民支出情况的调查数据”以及“某年某时间段我国17个地区降水中离子浓度和pH值浓度的检测结果”;借助SAS对两个实例的数据进行了无序样品聚类分析,给出了分档的结果,并对SAS输出结果做出了解释。
英文摘要:
      The purpose of this article was to introduce the basic concepts, calculation methods, two examples and the implementation of SAS calculation methods related to cluster analysis of disordered samples. The basic concepts included disordered samples and ordered samples, cluster analysis and comprehensive evaluation, high superiority indicators, low superiority indicators and expected indicators, sorting and grading, and standardized transformation. The calculation method involved the comprehensive scoring methods calculation formula based on expert ratings and the comprehensive scoring methods calculation formula based on variable observations. The data in the two examples were "survey data on the expenditure of farmers in 16 regions of China in 1982" and "detection results of ion concentration and pH value concentration in precipitation in 17 regions of China during a certain period of time in a certain year". Using SAS software, cluster analysis of disordered samples was performed on the data from two instances, furthermore, the graded results were provided, along with an explanation of the SAS output results.
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