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Submersible-Search-Model

潜水器位置预测和搜素救援模型

该模型用于解决2024数模美赛B题


以下为文件功能说明,具体模型得看论文呢

1. terrain.py

将只含有网格状高程数据的数据集制成三维地形图

数据集生成方法

  1. 获取对应地区的DEM文件(例如asc)

  2. 将asc文件的前六行数据参数去除

  3. 将asc文件每行数据前的空格删除(toData.py功能)

2. toData.py

去除asc文件每行数据前的空格

3. current.py

生成随机有规律的洋流方向和速度

4. mist.py (创新)

利用 Metropolis-Hastings 算法根据数据集生成某时间的点在三维空间的分布概率(我们称之为雾状图)

5. predict.py (核心算法1)

首先利用已构建的潜水器4自由度模型,模拟出潜水器的运动轨迹

然后利用MH算法生成潜水器某时刻在海中的概率分布图

6. search.py (核心算法2)

根据已有搜救模型,实现搜救模拟,得到搜救概率与时间函数


最后抒发一些感慨:

打数模真的是一件累活,在这4天中真的从早忙到晚,最后一天还得通宵。

不过我觉得还是有必要的。 因为自认为自己比较适合这类比赛,就是在一段时间内专心只搞一件事。

在这段时间内我可以完全投入,沉浸于心流状态,还能学到非常多的知识,至少比那应试教育有意思多了。

参加这比赛也是想要证明自己吧,以前可能真的太低估自己了。加油吧。

希望能获得个好成绩!

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