[1]徐楠1,2,孟宪举1,等.顾客需求模板的动态分类树研究[J].山东建筑大学学报,2014,(06):520-524.
 Xu Nan,Meng Xianju,et al.Research on dynamic classified trees for customer demand model[J].Journal of Shandong jianzhu university,2014,(06):520-524.
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顾客需求模板的动态分类树研究
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《山东建筑大学学报》[ISSN:1673-7644/CN:37-1449/TU]

卷:
期数:
2014年06期
页码:
520-524
栏目:
研究论文
出版日期:
2014-12-15

文章信息/Info

Title:
Research on dynamic classified trees for customer demand model
作者:
徐楠孟宪举李国斌
1.山东建筑大学机电工程学院,山东 济南 250101;2.山东省高校机械工程创新技术重点实验室,山东 济南 250101
Author(s):
Xu Nan 1 2 Meng Xianju 1 2 Li Guobin 1
1. School of Mechanical and Electronic Engineering, Shandong Jianzhu University, Jinan 250101, China; 2. Key Laboratory of Mechanical Engineering & Innovation Technology in Universities of Shandong, Jinan 250101, China
关键词:
质量功能配置顾客需求模板动态分类树二叉树最近相邻策略
Keywords:
quality function deployment customer demand model dynamic classified trees binary tree nearest neighbor strate
分类号:
TP391
文献标志码:
A
摘要:
顾客需求模板是质量功能配置(QFD)系统对设计实例和规则进行规范化的工具。文章基于质量功能配置中顾客需求动态获取的特点,分析了顾客需求模板实例提取和动态进化过程,规范了设计实例及设计规则的描述,提出了实现模板动态进化的动态分类树的概念,探讨了动态分类树的存储、规则调整方式以及实例归类方法。结果表明:基于数据结构的二叉树定义,将动态分类树的存储设计为三重链接方式,实例规则调整采用自下而上的方式检索规则并存储,实现系统存储的近似最小变量空间;基于最近相邻策略设计实例归类标准及其算法,通过指定归类标准值达到调整顾客需求模板中实例分类的目的,提高推理决策的准确性。
Abstract:
Customer demand model is a kind of tool to standardize design cases and rules of quality function deployment( QFD) . Based on the characteristics of obtaining customer demands in quality function deployment, the case collection and dynamic evolution process were analyzed and design case rulers were specified. The concept of dynamic classified trees was proposed to realize dynamic evolution of models. The storage model, rule adjustment and cases classification methods of dynamic classified trees were discussed. The results show that the storage model of dynamic classified trees was designed to triply links based on binary tree of data structure. To retrieve and store case rules bottom up approach of adjustment rules were applied and the approximate minimum variable space were achieved. The cases classification standards and algorithm were established according to nearest neighbor algorithm. By specifying the classification standards value to adjust the samples classification in customer demand model, the accuracy of inference and decisionmaking were improved.
更新日期/Last Update: 2015-02-01