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optimal stationing with k-means Algorithm |
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| XxneedhelpxX |
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Anmeldedatum: 28.12.21
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Verfasst am: 28.12.2021, 14:18
Titel: optimal stationing with k-means Algorithm
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Hello,
I have to find out the optimal stationing of rescue helicopters for my project work. I have to solve the task with the help of the k-means algorithm.
There are 3 helicopters available and there are 109 ski resorts.
The question is where these helicopters should be stationed.
The locations of the ski areas are given in x and y coordinates and the accident frequency of the ski areas is given as a number.
There are several possible solutions, however, I am to realize the weighted averaging as a solution approach.
This task is to be solved with the help of the k-means algorithm. The pseudo code is as follows:
1. choose number of desired clusters (here K rescue helicopters).
2. choose K random ski resorts as possible rescue helicopter locations
3. calculate distance of all ski areas to the selected helicopter locations
4. ski resorts are assigned to the helicopter location with the least distance
5. determine the weighted average (also called centroid) of each cluster.
6. choose as new cluster points or helicopter locations the ski resorts with the smallest distance to each centroid
7. if the clusters differ, repeat (3)-(6). If nothing has changed since the last run, abort.
8. END
I would really appreciate some help with the k-means algorithm, of course the solution would be perfect, but just an idea or an illustration of what the algorithm must look like will do just fine.
Of course the algorithm must work in Matlab.
Thank you
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| Harald |
Forum-Meister
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Beiträge: 24.495
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Version: ab 2017b
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Verfasst am: 28.12.2021, 16:35
Titel:
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Bitte keine Doppelposts, siehe
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