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基于数据的K均值理论及其应用(
)
《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]
- 卷:
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第44卷
- 期数:
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2021年02期
- 页码:
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10-17
- 栏目:
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·数学·
- 出版日期:
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2021-06-30
文章信息/Info
- Title:
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Application of K-Means Theory Based on Data
- 文章编号:
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1001-4616(2021)02-0010-08
- 作者:
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杨 金1; 陈 林1; 周 强2; 陈建勋1
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(1.重庆交通大学数学与统计学院,重庆 400074)(2.重庆南开中学,重庆 400074)
- Author(s):
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Yang Jin1; Chen Lin1; Zhou Qiang2; Chen Jianxun1
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(1.Chongqing Jiaotong University,Chongqing 400074,China)(2.Chongqing Nankai Middle School,Chongqing 400074,China)
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- 关键词:
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- Keywords:
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- 分类号:
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O175.13
- DOI:
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10.3969/j.issn.1001-4616.2021.02.003
- 文献标志码:
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A
- 摘要:
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首先使用主成分分析方法对车辆行驶工况的特征参数进行处理,然后利用K-均值聚类原理对所有具有代表性的运动学片段进行聚类分析,由此得出汽车行驶工况的数学原理. 为汽车节能减排的发展和建立能够正确反映我国道路工况特征的行驶工况提供理论依据.
- Abstract:
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In this paper,the principal component analysis method is used to process the characteristic parameters of vehicle driving conditions,and the K-means clustering principle is used to cluster all the representative kinematics fragments,and then the mathematical principle of vehicle driving conditions is obtained. It provides a theoretical basis for the development of automobile energy saving and emission reduction and the establishment of driving conditions that can accurately reflect the characteristics of road conditions in China.
更新日期/Last Update:
2021-06-30