1) inverse distance weighting(IDW) method
反距离权重法(IDW)
2) inverse distance weighing
反距离权重法
1.
Annual average temperature data,annual rainfall and annual accumulated temperature data from 2114 meteorological stations in China and surrounding countries from 1961 to 1990 were interpolated by using inverse distance weighing(IDW),ordinary kriging(OK)and spline with ArcMap.
基于地理信息系统软件ArcMap的统计分析模块,对我国及周边地区2114个气象站点1961—1990年的年均温度、年降水量以及年积温等数据,分别使用反距离权重法、样条函数法和普通克里格法,选取不同的气象站点进行了空间插值,并利用交叉检验方法对插值精度进行了评估,结果表明:对于同一种插值方法,参与插值的气象站点数目不同,插值结果也不同。
3) inverse distance weighted(IDW)
距离反比权重算法
1.
In this paper,we discuss a method based on inverse distance weighted(IDW) algorithm to construct seafloor digital terrain model(DTM) using multi-beam soundings,and the application of level of details(LOD) technology.
针对多波束测深数据集,采用改进的距离反比权重算法和多细节层次模型技术来建立海底数字地形模型(DTM)。
4) distance-weighted method
距离权重法
1.
This paper introduces the solution to the problem C of 2005 Higher education press cup CUMCM,the distance-weighted method of predicted rainfall in the observation stations,and gives the comparisons between distance-weighted method and the interpolation.
给出了确定观测站点预报雨量的距离权重法与插值法,并进行了比较。
5) inverse distance weighted interpolation
反距离权重插值
1.
According to the research status at home and abroad, the paper chose the Ordinary Kriging, Regression Kriging and Inverse Distance Weighted Interpolation methods to analysis soil nutrients spatial variability characteristics and distribution pattern in Jiutai County.
普通克吕格法和反距离权重法对于土壤养分分布趋势的反映上基本是一致的,反距离权重插值的精度要高于普通克吕格插值的精度,说明九台市土壤养分的空间分布预测研究更适合采用反距离权重方法。
6) inverse distance weighting
反距离加权法
1.
The three spafial interpolation methods are applied to the rainfall spatial interporation for the Qingjiang River basin: ordinary Kriging,co-Kriging and inverse distance weighting(IDW).
将普通克里格法、协同克里格法和反距离加权法3种空间插值方法应用于清江流域的降雨空间插值,比较了它们的应用效果,并分析了它们插值效果不同的原因。
2.
The different methods of interpolation principle were studied,such as inverse distance weighting (IDW),radial basis functions (RBF),and Kriging.
该文通过比较反距离加权法、径向基函数法、克里格法等插值方法的异同,以调查县夏播玉米5个阶段的生育期为数据源,对黄淮海夏播玉米区生育期的数据进行空间插值处理,并使用交叉验证对表面精度进行分析。
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