文献类型：期刊文献

英文题名：Attribute Normalization Approaches to Group Decision-making and Application to Software Reliability Assessment

作者：Yue, Chuan[1]

机构：[1]Guangdong Ocean Univ, Coll Math & Comp Sci, Zhanjiang, Peoples R China

年份：2021

卷号：13

期号：1

起止页码：139

外文期刊名：COGNITIVE COMPUTATION

收录：SCI-EXPANDED(收录号：WOS:000515855000001)、、EI(收录号：20200708156308)、Scopus(收录号：2-s2.0-85079192217)、WOS

基金：This study was funded by the Young Creative Talents Project from Department of Education of Guangdong Province (No. 2016KQNCX064), the Project of Enhancing School with Innovation of Guangdong Ocean University (No. GDOU2017052802), the Project of Professional Core Course from College of Mathematics and Computer Science, Guangdong Ocean University (No. 571119134), and the Project of Teaching Innovation in 2019 from Guangdong Ocean University (No. 570219088).

语种：英文

外文关键词：Normalization; Multi-attribute decision-making; Group decision-making; Normalized projection; Software reliability assessment

外文摘要：A group decision-making (GDM) process is a social cognition process, which is a sub-topic of cognitive computation. The normalization of attribute values plays an important role in multi-attribute decision-making (MADM) and GDM problems. However, this research finds that the existing normalization methods are not always reasonable for GDM problems. To solve the problem of attribute normalization in GDM systems, some new normalization models are developed in this paper. An integrative study contributes to cognitive MADM and GDM systems. In existing normalization models, there are some bounds, such as Max(uj),Min(uj), n-ary sumation (uj),and n-ary sumation (uj)2. They are limited to a single attribute vector u(j). The bound of new normalization method proposed in this work is related to one or more attribute vectors, in which the attribute values are graded in the same measure system. These related attribute vectors may be distributed to all decision matrices graded by this decision system. That is, the new bound in developed normalization model is an uniform bound, which is related to a decision system. For example, this uniform bound can be written as one of Max(.),Min(.), n-ary sumation (.), n-ary sumation (.)2\documentclass[12pt]{minimal} (.)<<^>>{2}}$\end{document}. Some illustrative examples are provided. A practical application to the evaluation of software reliability is introduced in order to illustrate the feasibility and practicability of methods introduced in this paper. Some experimental and computational comparisons are provided. The results show that new normalization methods are feasibility and practicability, and they are superior to the classical normalization methods. This work has provided some new normalization models. These new methods can adapt to all decision problems, including MADM and GDM problems. Some important limitations and future research are introduced.