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Urban GIS and charging station data

Citation Author(s):
Milan
Straka
Lubos
Buzna
Gijs
van der Poel
Submitted by:
Milan Straka
Last updated:
Tue, 05/17/2022 - 22:21
DOI:
10.21227/69hf-9c82
Data Format:
.csv
Link to Paper:
Predicting Popularity of Electric Vehicle Charging Infrastructure in Urban Context
License:
Creative Commons Attribution
1353 Views
Categories:
Machine Learning
Transportation
Energy
Power and Energy
Social Sciences
Keywords:
Electric Vehicles, GIS, POI; Ratings; Geographical coordinates, charging stations
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Abstract 

Dataset consists of various open GIS data from the Netherlands as Population Cores, Neighbhourhoods, Land Use, Neighbourhoods, Energy Atlas, OpenStreetMaps, openchargemap and charging stations. The data was transformed for buffers with 350m around each charging stations. The response variable is binary popularity of a charging pool.

Instructions: 

Use the first n_RFID variable as a response, the rest as predictors.

Comments

very good. thank you

Submitted by Behrouz Mehdiza... on Sat, 10/16/2021 - 06:59

Is there any dictionary that explains what each variable means?

Submitted by Alvaro Corrales Cano on Mon, 03/21/2022 - 07:03

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