| 相似单元堤段模糊聚类分析 |
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| 引用本文： | 傅蜀燕,欧斌,林志祥,高胜松.相似单元堤段模糊聚类分析[J].水利经济,2018,36(3):6-9. |
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| 作者姓名： | 傅蜀燕 欧斌 林志祥 高胜松 |
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| 作者单位： | 南京水利科学研究院水文水资源与水利工程科学国家重点实验室;云南农业大学水利学院;云南省水利厅工程管理局;云南农业大学机电工程学院 |
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| 基金项目： | 水文水资源与水利工程科学国家重点实验室开放基金(2016491811,2017491811)；云南省教育厅科学研究基金(2016ZZX109) |
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| 摘 要： | 对堤防工程采取单元堤段相似性分类便于堤防的安全评价与管理。在划分单元堤段的基础上,拟定单元堤段的属性指标,基于模糊聚类理论对单元堤段的属性指标进行定量指标和定性指标相似性组合度量,构建单元堤段模糊相似矩阵,再通过平方法计算出模糊相似矩阵对应的模糊等价矩阵。通过调整模糊等价矩阵的阈值,获得不同单元堤段的分类组合,再结合混合F统计方法和模糊划分熵确定最佳分类数。
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| 关 键 词： | 堤防 单元堤段 属性指标 模糊聚类 分类 |
| 收稿时间： | 2017/12/28 0:00:00 |
Fuzzy clustering analysis of similarity unit embankments |
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| FU Shuyan,OU Bin,LIN Zhixiang and GAO Shengsong.Fuzzy clustering analysis of similarity unit embankments[J].Journal of Economics of Water Resources,2018,36(3):6-9. |
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| Authors: | FU Shuyan OU Bin LIN Zhixiang and GAO Shengsong |
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| Institution: | State Key Laboratory of Hydrology, Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210098, China;College of Water Conservancy, Yunnan Agricultural University, Kunming 650201, China,College of Water Conservancy, Yunnan Agricultural University, Kunming 650201, China,College of Water Conservancy, Yunnan Agricultural University, Kunming 650201, China;Engineering Management Bureau, Department of Water Resources of Yunnan Province, Kunming 650021, China and College of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming 650201, China |
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| Abstract: | The similarity classification of unit embankments can be used for the safety evaluation and management of embankment engineering. On the basis of division of the unit embankments and their attribute indexes are drafted. According to the fuzzy clustering theory, the attribute indexes of the unit embankments are measured by quantitative and qualitative indexes. The fuzzy similarity matrix for the unit embankments is established, and the relevant fuzzy equivalent matrix is calculated by using the square method. By adjusting the threshold of the fuzzy equivalent matrix, the similarity classifications of different unit embankments are obtained, and then the optimal classification number is determined by combining the mixed F statistical method and the fuzzy partition entropy. |
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| Keywords: | embankment unit embankment attribute index fuzzy clustering classification |
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