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中国管理科学 ›› 2015, Vol. 23 ›› Issue (9): 132-138.doi: 10.16381/j.cnki.issn1003-207x.2015.09.016

• 论文 • 上一篇    下一篇

基于灰色变化率关联度的灰色趋势分析模型的构建及应用

李雪梅1, 党耀国2, 金镭3   

  1. 1. 中国海洋大学经济学院, 山东 青岛 266100;
    2. 南京航空航天大学经济与管理学院, 江苏 南京 211106;
    3. 中国石油大学工商管理学院, 北京 102249
  • 收稿日期:2014-01-16 修回日期:2014-12-28 出版日期:2015-09-20 发布日期:2015-09-28
  • 作者简介:李雪梅(1985-),女(汉族),山东邹平人,中国海洋大学经济学院讲师,研究方向:灰色系统理论与应用、海洋经济.
  • 基金资助:

    国家社会科学基金重大资助项目(14ZDB151);国家自然科学基金资助项目(71371098);中央高校基本科研业务费专项资金(NC2012001);江苏高校哲学社会科学重点研究基地重大资助项目(2012JDXM005);江苏省普通高校研究生科研创新计划(CXZZ12_0174);南京航空航天大学博士学位论文创新与创优基金(BCXJ12-11)

The Research on Formation Mechanism of Customer Loyalty under the Shopping Online

LI Xue-mei1, DANG Yao-guo2, JIN Lei3   

  1. 1. College of Economics, Ocean University of China, Qingdao 266100, China;
    2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China;
    3. School of Business and Administration, China University of Petroleum, Beijing 102249, China
  • Received:2014-01-16 Revised:2014-12-28 Online:2015-09-20 Published:2015-09-28

摘要: 为了考察序列间动态变化趋势的相似性,提出了衡量变化率接近程度的灰色变化率关联度,并讨论了灰色变化率关联度的性质,进而基于变化率关联度提出了灰关联空间分解的新方法。根据行为序列与特征序列变化率正负性的一致性,构建空间分解指数,对灰关联空间进行分解,对特征序列与行为序列进行灰色趋势分析,识别出与特征序列的变化趋势基本保持同步的行为序列。既能够根据变化率关联度对全体行为序列进行排序,也可以在子空间内部再根据变化率关联度进行排序,从而分别在同步子空间与异向子空间识别出关键因素与次要因素。最后将基于变化率关联度的灰色趋势分析应用于阜新煤炭产业集群关键影响因素的识别中,并与其它关联度结果进行了对比分析,验证了本文模型的有效性。

关键词: 变化率关联度, 空间分解, 趋势分析

Abstract: In order to measure the similarity in the change trends between sequences, the grey change rate relational analysis (C-GRA) model has been established. The properties of the C-GRA model such as are studied in this paper. To research the consistency of the change direction between sequences, a new method for space decomposition has been put forth based on the C-GRA model with sign functionssgn (y0(tkyi(tk)). According to the consistency of positive or negative changes, the space decomposition index was proposed as Pi=sgn2[sgn1y0(tkyi(tk)], and the space was decomposed. Then, a grey trend analysis on the characteristic and behavioral sequences was performed to identify the sequences that shared the same step with the characteristics sequence. It should be noted that the entire ranking of the behavior sequences are not the only data that can be obtained;rather, the rankings in separate spaces can also be obtained, so the key factors in the promotion subspace, the inhibition subspace, and the coordinate subspace are clear. In the last part of this paper, the factors that affect the production of coal in the city of Fuxin are studied using the grey trend analysis, as based on the C-GRA model. Date is from the government of Fuxin. This application is presented to illustrate the effectiveness and practicality of the proposed model.

Key words: grey relational drgree with rate of change, space decomposition, trend analysis

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