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Home Page: http://tofill.dyndns.info:7080
License: MIT License
Predicting the optimal strategy for fueling for a given route
Home Page: http://tofill.dyndns.info:7080
License: MIT License
In the moment you can only set the time but not the date
Maybe we can find out something interesting when looking on the first occurrence of a gas station
Explore in our data what the maximum distance of a gas station to an Autobahn is that we would say it's a "Autobahn gas station"
"Erstellen Sie Fahrzeugrouten, von denen Sie annehmen, dass Ihr Programm im Vergleich zu denen anderer Teams gute Ergebnisse liefert."
e.g. Given a start and an end point, a tank size and the average consumption, compute the fueling stops for the itinerary showing the fuel stations, how much to fuel and the overall price in the end.
Compare some gas stations at the Autobahn, with is effected by commuter traffic, economically underdeveloped areas (Brandenburg)...
Section "Zeitreihenanalyse"
"Überlegen Sie sich dazu den möglichen Einfluss von Merkmalen einer Tankstelle auf die Entwicklung ihrer Benzinpreise (z.B. Tankstellen an Autobahnen, Tankstellen die vom Berufsverkehr erfasst werden oder Tankstellen in wenig erschlossenen Regionen)."
We could use this package https://github.com/DinoTools/python-overpy to run the queries
Mail an Ludger
Mismatch between numbering and references of figures.
with pyunicorn
Integrate oil and gasoline prices in prediction
Proof of concept notebook: https://github.com/WGierke/informatiCup2018/blob/master/notebooks/1.0-sb-oil_prices.ipynb
Problem: We don't have the future oil price if we predict the gas price at a gas station
One usually only has to download this data once and this clearly doesn't justify using the LFS bandwith for it.
According to the task:
Ihre Implementierung muss für die Vorhersage von Benzinpreisen für gegebene Tankstellen und für
die Ausgabe einer Tankstrategie "Plain text"-Dateien in den folgenden beiden Dateiformaten
ausgeben
we should not only output the perfect fueling strategy but also gas price predictions only.
We currently only have holidays as features. How can we respect features that are not just dates but also e.g. time series (like the international gas price, ...)?
This is extracted from #15 since it needs more work than expected.
Given the near gas stations at the itinerary, the starting time and the tank size from the front-end...
Prediction on the web server doesn't use multiple cores. It utilises only one core.
Make some data exploration and write a bit about it
Section "Zeitreihenanalyse"
"Analysieren Sie zunächst die historischen Benzinpreise seit Beginn der Meldepflicht im Jahr 2013"
Refer to the docs for details.
Add option to set the desired fuel level at the destination, otherwise we'll have a breakdown there
for landuse in [industrial, commercial, farmland, farmyard, residential, retail]
rel
(around:1000, 50.08232, 8.54354)
["landuse"="industrial"];
(._;>;);
out body;
http://overpass-turbo.eu/s/tjT
Returns points with coordinates, have to query if gas station is in this polygon
Feature could by noisy
Is this a comma fault or a very high prediction?
{'end': (48.401030000000006, 9.98764), 'name': ['Aral Tankstelle'], 'start': (52.390530000000005, 13.064540000000001), 'address': ['B 100\n6796 Brehna'], 'overall_price': 42005.76141429667, 'fill_liters': [32.512199237071727], 'prices': [1292.0], 'payment': [42005.76141429667], 'stops': [(51.5537376, 12.1966591)]}
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