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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Shepard's method ： ウィキペディア英語版 Inverse distance weighting Inverse Distance Weighting (IDW) is a type of deterministic method for multivariate interpolation with a known scattered set of points. The assigned values to unknown points are calculated with a weighted average of the values available at the known points. The name given to this type of methods was motivated by the weighted average applied, since it resorts to the inverse of the distance to each known point ("amount of proximity") when assigning weights. ==Definition of the Problem== The expected result is a discrete assignment of the unknown function $u$ in a study region: $u(x):\; x\; \backslash rightarrow\; \backslash mathbb,\; \backslash quad\; x\; \backslash in\; \backslash mathbf\; \backslash sub\; \backslash mathbb^n$ where $\backslash mathbf$ is the study region. The set of $N$ known data points can be described as a list of tuples: $(u\_1),\; (x\_2,\; u\_2),\; ...,\; (x\_N,\; u\_N))$ The function is to be "smooth" (continuous and once differentiable), to be exact ($u(x\_i)=u\_i$) and to meet the user's intuitive expectations about the phenomenon under investigation. Furthermore, the function should be suitable for a computer application at a reasonable cost (nowadays, a basic implementation will probably make use of parallel resources). 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Inverse distance weighting」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.