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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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Traffic Weekly Dataset

Authors: Godahewa, Rakshitha; Bergmeir, Christoph; Webb, Geoff; Hyndman, Rob; Montero-Manso, Pablo;

Traffic Weekly Dataset

Abstract

{"references": ["Caltrans, 2020. Caltrans performance measurement system, california department of transportation. Accessed: 2020-04-30. URL http://pems.dot.ca.gov/", "Lai, G., Chang, W., Yang, Y., Liu, H., 2017. Modeling long and short-term temporal patterns with deep neural networks. CoRR abs/1703.07015.URL http://arxiv.org/abs/1703.07015", "Lai, G., 2017. multivariate-time-series-data. https://github.com/laiguokun/multivariate-time-series-data, accessed: 2020-05-04"]}

This dataset contains an aggregated version of the San Francisco Traffic dataset used by Lai et al. (2017). It contains 862 weekly time series showing the road occupancy rates on the San Francisco Bay area freeways from 2015 to 2016.

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Keywords

San Francisco Traffic, forecasting, weekly series

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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