Generalized interval grey entropy weight distribution for combining cases indicators

被引：0
|
作者：
Zhang Q. [1 ,2 ]
Fang Z. [1 ,2 ]
Tao L. [1 ,2 ]
Liu S. [1 ,2 ]
机构：
[1] College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing
[2] Institute of Grey System, Nanjing University of Aeronautics and Astronautics, Nanjing
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2018年 / 38卷 / 08期
关键词：
Combining cases; Generalized interval grey entropy; Generalized standard interval grey number; Multi-uncertainty; Weight distribution;
D O I：
10.12011/1000-6788(2018)08-2057-11
中图分类号：
学科分类号：
摘要：
Combining cases mean clustering the series cases which the one or a group of criminals make.The information of combining cases are mainly from the victims, witnesses and police officers, so under the emergency situation, reflection and description of the case has a strong uncertainty, leading to information has the characteristics of multi-uncertainty. However there is the certain limitation for traditional method of multiple attribute clustering decision to research combining cases. In this paper, we study on the weight distribution of combining cases indicators deeply. At first, we take the combining cases as research object,point out the combining cases is typical multi-uncertainty case, and propose all uncertain parameters can be unified into the generalized standard interval grey numbers under a specific condition. Then we establish the generalized gray similarity model to calculate the similarity of attribute index as well as the whole case,and build the generalized interval grey entropy weight distribution model for combining cases indicators to solve the indicator weight of combining cases. Finally through the case study, we prove the rationality and feasibility of the model in this paper. © 2018, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
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页码：2057 / 2067
页数：10
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