Publication type: | Conference paper |
Type of review: | Peer review (abstract) |
Title: | Improving the forecast of freight transport demand using machine learning and time series analysis |
Authors: | Bruckmann, Dirk Jackson, Clare Ott, Thomas Weidmann, Ulrich |
Conference details: | 14th Swiss Transport Research Conference, Ascona, 14-16 May 2014 |
Issue Date: | 2014 |
Language: | English |
Subject (DDC): | 003: Systems |
URI: | https://digitalcollection.zhaw.ch/handle/11475/4397 |
Fulltext version: | Published version |
License (according to publishing contract): | Licence according to publishing contract |
Departement: | Life Sciences and Facility Management |
Organisational Unit: | Institute of Computational Life Sciences (ICLS) |
Appears in collections: | Publikationen Life Sciences und Facility Management |
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Bruckmann, D., Jackson, C., Ott, T., & Weidmann, U. (2014). Improving the forecast of freight transport demand using machine learning and time series analysis. 14th Swiss Transport Research Conference, Ascona, 14-16 May 2014.
Bruckmann, D. et al. (2014) ‘Improving the forecast of freight transport demand using machine learning and time series analysis’, in 14th Swiss Transport Research Conference, Ascona, 14-16 May 2014.
D. Bruckmann, C. Jackson, T. Ott, and U. Weidmann, “Improving the forecast of freight transport demand using machine learning and time series analysis,” in 14th Swiss Transport Research Conference, Ascona, 14-16 May 2014, 2014.
BRUCKMANN, Dirk, Clare JACKSON, Thomas OTT und Ulrich WEIDMANN, 2014. Improving the forecast of freight transport demand using machine learning and time series analysis. In: 14th Swiss Transport Research Conference, Ascona, 14-16 May 2014. Conference paper. 2014
Bruckmann, Dirk, Clare Jackson, Thomas Ott, and Ulrich Weidmann. 2014. “Improving the Forecast of Freight Transport Demand Using Machine Learning and Time Series Analysis.” Conference paper. In 14th Swiss Transport Research Conference, Ascona, 14-16 May 2014.
Bruckmann, Dirk, et al. “Improving the Forecast of Freight Transport Demand Using Machine Learning and Time Series Analysis.” 14th Swiss Transport Research Conference, Ascona, 14-16 May 2014, 2014.
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