首页 | 本学科首页   官方微博 | 高级检索  
     

犹豫模糊群共识实现算法及其数据系统优选
引用本文:陈雪娟. 犹豫模糊群共识实现算法及其数据系统优选[J]. 计算机工程与应用, 2021, 57(11): 128-134. DOI: 10.3778/j.issn.1002-8331.2101-0238
作者姓名:陈雪娟
作者单位:广东理工学院 信息技术学院,广东 肇庆 526114
摘    要:针对犹豫模糊偏好关系(HFPR)可以在复杂的管理环境下全面描述专家的犹豫评价信息的优势,基于HFPR构建了一种犹豫模糊群共识实现算法,并将其应用于银行数据系统的选购过程中。引入一种新的一致性指数方法来衡量个体HFPR的一致性水平;为了提升群体专家对决策结果的满意度,设计了一种犹豫模糊群共识实现算法,该算法能够在群体HFPR达到共识水平的情况下保证个体HFPR仍然具有满意一致性;通过银行数据系统的选购实例和对比分析实验说明了提出的方法的实用性和有效性。

关 键 词:犹豫模糊偏好关系  一致性  共识性  数据系统  

Hesitant Fuzzy Group Consensus Reaching Algorithm and Its Application to Select Data System
CHEN Xuejuan. Hesitant Fuzzy Group Consensus Reaching Algorithm and Its Application to Select Data System[J]. Computer Engineering and Applications, 2021, 57(11): 128-134. DOI: 10.3778/j.issn.1002-8331.2101-0238
Authors:CHEN Xuejuan
Affiliation:College of Information Technology, Guangdong Polytechnic College, Zhaoqing, Guangdong 526114, China
Abstract:With respect to the advantage that Hesitant Fuzzy Preference Relation(HFPR) can fully describe experts’ hesitant evaluation information in complex management environment, a hesitant fuzzy group consensus reaching algorithm based on HFPR is constructed and applied to the purchase process of bank data system. Firstly, a new consistency index method is introduced to measure the consistency level of the individual HFPR. Then, in order to improve the satisfaction of group experts for decision-making results, a hesitant fuzzy group consensus reaching algorithm is designed, which can ensure that the individual HFPR still has satisfactory consistency when a group HFPRs reach the consensus level. Finally, the example and comparative analysis experiment of bank data system are provided to show the practicability and effectiveness of the proposed method.
Keywords:hesitant fuzzy preference relation  consistency  consensus  data system  
点击此处可从《计算机工程与应用》浏览原始摘要信息
点击此处可从《计算机工程与应用》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号