On modeling mechanisms and applicable ranges of grey incidence analysis models

入射(几何) 亲密度 学位(音乐) 数学 统计 计算机科学 数学分析 物理 几何学 声学
作者
Wenjie Dong,Sifeng Liu,Zhigeng Fang
出处
期刊:Grey systems [Emerald Publishing Limited]
卷期号:8 (4): 448-461 被引量:19
标识
DOI:10.1108/gs-04-2018-0019
摘要

Purpose The purpose of this paper is to study the modelling mechanisms of several grey incidence analysis models with great influence, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model; then analyse the problems to be solved in grey incidence analysis models; and clarify the applicable ranges of commonly used grey incidence models. Design/methodology/approach The paper comes to conclusions by means of comparable analysis. The authors compare several commonly used grey incidence analysis models, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model and give several examples to clarify the reasons why quantitative analysis results of different models are not exactly the same. Findings As the intension of each kind of incidence model is clear and the extension is relatively obscure, grey incidence orders calculated by different incidence models are often different. When making actual decisions, incompatible results may appear. According to different characteristics of extraction, grey incidence analysis models can be divided into three types: incidence model based on closeness perspective, incidence model based on similarity perspective and incidence model based on comprehensive perspective. Practical implications The conclusions obtained in this paper can help people avoid some defects in the process of actual selection and choose the better incidence analysis model. Originality/value The conclusions can be used as a reference and basis for the selection of grey incidence analysis models, it can help to overcome the defects and shortcomings of models caused by themselves and screen out more excellent analytical models.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
零点起步完成签到,获得积分10
3秒前
ChatGPT发布了新的文献求助10
3秒前
轻松寒荷完成签到,获得积分10
4秒前
小兔叽完成签到 ,获得积分10
7秒前
9秒前
10秒前
香蕉觅云应助JingMa采纳,获得10
14秒前
15秒前
Licyan完成签到,获得积分10
16秒前
Ava应助Ausna采纳,获得10
17秒前
这杯酒名忘情完成签到,获得积分10
17秒前
18秒前
搜集达人应助SHUAI采纳,获得10
18秒前
18秒前
甜蜜的振家完成签到,获得积分10
20秒前
心理可达鸭完成签到,获得积分10
21秒前
22秒前
23秒前
苏打完成签到 ,获得积分10
23秒前
刀刀发布了新的文献求助10
24秒前
25秒前
Homura完成签到,获得积分10
25秒前
26秒前
xiaohei完成签到,获得积分10
26秒前
含蓄思柔发布了新的文献求助10
26秒前
Magic完成签到 ,获得积分10
26秒前
26秒前
27秒前
飞快的邴完成签到,获得积分10
27秒前
科研通AI2S应助Xu采纳,获得10
28秒前
Lilili完成签到 ,获得积分10
28秒前
30秒前
Sir.夏季风完成签到,获得积分10
30秒前
独特的凝云完成签到 ,获得积分0
31秒前
arniu2008发布了新的文献求助30
32秒前
最棒的宝宝完成签到,获得积分10
32秒前
称心的板栗完成签到,获得积分10
34秒前
喜喜不嘻嘻完成签到,获得积分10
36秒前
wpt关注了科研通微信公众号
36秒前
海盗船长完成签到,获得积分10
39秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359032
求助须知:如何正确求助?哪些是违规求助? 8173002
关于积分的说明 17212025
捐赠科研通 5414024
什么是DOI,文献DOI怎么找? 2865338
邀请新用户注册赠送积分活动 1842737
关于科研通互助平台的介绍 1690836