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基于正交试验选优的湖底地形分区插值方法

龚懿 陈再扬 张维 汪靓 王玉琳 杨小玲

龚懿,陈再扬,张维,等. 基于正交试验选优的湖底地形分区插值方法[J]. 水利水运工程学报. doi:  10.12170/20211103004
引用本文: 龚懿,陈再扬,张维,等. 基于正交试验选优的湖底地形分区插值方法[J]. 水利水运工程学报. doi:  10.12170/20211103004
(GONG Yi, CHEN Zaiyang, ZHANG Wei, et al. Research on interpolation method of lake terrain zoning based on orthogonal experiment Optimization[J]. Hydro-Science and Engineering(in Chinese)) doi:  10.12170/20211103004
Citation: (GONG Yi, CHEN Zaiyang, ZHANG Wei, et al. Research on interpolation method of lake terrain zoning based on orthogonal experiment Optimization[J]. Hydro-Science and Engineering(in Chinese)) doi:  10.12170/20211103004

基于正交试验选优的湖底地形分区插值方法

doi: 10.12170/20211103004
基金项目: 国家自然科学基金资助项目(51909230);江苏省水利科技重点项目(2020011);中国博士后科学基金资助项目(2019M661948)
详细信息
    作者简介:

    龚 懿(1983—),男,江苏常熟人,副教授,博士,主要从事水利优化规划与管理研究。E-mail:gongyi_8@163.com

    通讯作者:

    汪 靓(E-mail:right628@126.com

  • 中图分类号: P343

Research on interpolation method of lake terrain zoning based on orthogonal experiment Optimization

  • 摘要: 为降低湖底高程采样点变异较大对插值计算的影响,获得精度较高的湖底地形,将高程采样点变异程度对插值的影响引入普通的反距离加权插值法中,提出了考虑高程采样点变异程度的湖泊地形分区插值方法。通过正交试验优化方法,得到各分区反距离最优幂值。以太湖为研究实例,对比了几种插值方法对太湖湖底地形的插值效果。结果表明分区域反距离加权插值法具有良好的适应性:在高程方面,经实测验证,其均方根误差最小;在库容方面,该方法与克里金法、反距离加权插值法、自然邻域法相比,平均相对误差分别减少0.97%、0.90%、1.37%,插值效果明显更优。因此,在湖泊地形起伏较大情况下,分区域反距离加权插值法能够获得较高精度的湖底形态,可用于不同类型的湖底地形插值计算。
  • 图  1  实测点空间分布

    Figure  1.  Spatial distribution of measured points

    图  2  太湖地形采样点局部起伏分布

    Figure  2.  Local undulation distribution map of Taihu Lake terrain sampling points

    图  3  L25(53)正交表区域幂值选优方案组合

    Figure  3.  L25(53) orthogonal table region power selection scheme combination

    图  4  太湖湖底地形空间展布

    Figure  4.  Spatial distribution of topography at the bottom of Taihu Lake

    表  1  4种空间插值方法的误差分析结果(高程)

    Table  1.   Error analysis results of four spatial interpolation methods (elevation)

    插值方法高程平均值最大相对误差/%均方根误差/m
    实测高程 −0.635 / /
    分区域反距离加权法 −0.637 93.24 0.144
    反距离加权法 −0.642 73.31 0.175
    克里金法 −0.640 89.42 0.178
    自然邻域法 −0.647 85.61 0.165
    下载: 导出CSV

    表  2  多种方法插值结果误差分析(库容)

    Table  2.   Error analysis of interpolation results by various methods (storage capacity)

    插值方法最大相对误差/%平均相对误差/%均方根误差∕亿m3
    分区域反距离加权法9.657.702.34
    反距离加权法16.298.672.47
    克里金法14.698.602.48
    自然邻域法16.269.072.72
    下载: 导出CSV
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  • 收稿日期:  2021-11-03

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