| 基于灰色关联度-云模型的群评价数据质量改进方法及应用研究 |
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| 引用本文： | 刘国栋,朱建军,刘小弟. 基于灰色关联度-云模型的群评价数据质量改进方法及应用研究[J]. 运筹与管理, 2021, 30(3): 144-150. DOI: 10.12005/orms.2021.0088 |
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| 作者姓名： | 刘国栋 朱建军 刘小弟 |
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| 作者单位： | 1.南京航空航天大学 经济与管理学院, 江苏 南京 211106; 2.临沂大学 物流学院, 山东 临沂 276005; 3.安徽工业大学 数理科学与工程学院, 安徽 马鞍山 243002 |
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| 基金项目： | 国家自然科学基金资助项目(71601002,72071106);教育部人文社科青年基金资助项目(16YJC630077);山东省高等学校教学改革研究项目(2015Z033)。 |
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| 摘 要： | 针对群评价中的数据质量问题, 从评价专家和评价值两个角度进行了异常数据处理, 提出了基于灰色关联度-云模型的群评价数据质量改进方法。基于改进的云距离模型测算被评价对象云和目标云之间的差距, 采用TOPSIS法进行评价排序。将数据质量改进方法和云距离模型用于区域物流竞争力群评价, 改进了群评价的数据质量, 提高了评价结果的稳定性和代表性。
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| 关 键 词： | 群评价 灰色关联度 云模型 数据质量 异常数据 |
| 收稿时间： | 2019-03-19 |
Research on Improvement Method and Application of Group Evaluation Data Quality Based on the Degree of Grey Incidence and Cloud Model |
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| LIU Guo-dong,ZHU Jian-jun,LIU Xiao-di. Research on Improvement Method and Application of Group Evaluation Data Quality Based on the Degree of Grey Incidence and Cloud Model[J]. Operations Research and Management Science, 2021, 30(3): 144-150. DOI: 10.12005/orms.2021.0088 |
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| Authors: | LIU Guo-dong ZHU Jian-jun LIU Xiao-di |
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| Affiliation: | 1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;2. School of Logistics, Shandong Linyi University, Linyi 276005, China;3. School of Mathematics and Physics, Anhui University of Technology, Ma’anshan 243002, China |
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| Abstract: | Aiming at the data quality problem in group evaluation,the outlier data processing is carried out from the perspectives of evaluation experts and evaluation values,and a data quality improvement method based on the degree of grey incidence and cloud model is proposed.Based on the improved cloud distance model,the gap between the evaluated object cloud and the target cloud is measured,and the TOPSIS method is used for ranking.The data quality improvement method and cloud distance algorithm are applied to group evaluation of the regional logistics competitiveness,which improves the data quality of the group evaluation and enhances the stability and representativeness of the evaluation results. |
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| Keywords: | group evaluation the degree of grey incidence cloud model data quality outlier data |
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