Say I ve上下了一个有记录的全球定位系统轨道。 有些人来自同一路线上的多次旅行,有些人来自完全独特的路线,有些路线是不同的路线,但有一些部分是共同的。
Given all this data, I want to:
假设1确实是2例。
举一个具体例子:假设你每天的全球定位系统轨道是大量自行车压缩机。 从这一数据中提取最受欢迎的自行车轮通勤走廊,其基础是实际脱节,而不是由地方政府制作的穿梭地图。
是否出版了这方面的算法? 他们如何工作? 论文和(或)法典的点人非常赞赏。
你可以使用3D的图表,在地图上找到最受访点。 利用你可以找到最常用的道路。
Detail: Keep a 2D matrix count and initialize it to 0, X[i,j]=0. For each track, increment X[i,j]s on the path. Once you have processed all the tracks, threshold this matrix to min threshold (what is the minimum number of tracks for it to be a repeated trip?).
一些实际细节: 假设你走了一条路。 可在以下两个要点之间找到一套要点:。 你们可能想用一个“这一cker线”来说明数据的性质。
这似乎是一个涉及许多地理信息系统问题的非常一般性的问题。
After some search, it seems you would need to apply some algorithms for computing the similarity between any two routes. Wang et al. (2013) analyzes a number of such measures. However, all these measures are implemented by dynamic programming with time complexity of O(N1N2), where N1 and N2 are the number of points in the two routes.
Mariescu-Istodor et al. (2017),其中每一条线路均在预定的电网系统中转变为一组电池。 该文件还把包容措施定义为另一个路线内的一个路线,这似乎与你所提问题的第二点有关。
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