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Using Machine Learn...
Using Machine Learning to Predict Freight Vehicles' Demand for Loading Zones in Urban Environments
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- Ludowieg, Andres Regal (författare)
- Universidad del Pacífico
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- Sanchez-Diaz, Ivan, 1984 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Kumar Kalahasthi, Lokesh, 1988 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2022-08-01
- 2023
- Engelska.
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Ingår i: Transportation Research Record. - : SAGE Publications. - 0361-1981 .- 2169-4052. ; 2677:1, s. 829-842
- Relaterad länk:
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- This paper studies demand for public loading zones in urban environments and seeks to develop a machine learning algorithm to predict their demand. Understanding and predicting demand for public loading zones can: (i) support better management of the loading zones and (ii) provide better pre-advice so that transport operators can plan their routes in an optimal way. The methods used are linear regression analysis and neural networks. Six months of parking data from the city of Vic in Spain are used to calibrate and test the models, where the parking data is transformed into a time-series format with forecasting targets. For each loading zone, a different model is calibrated to test which model has the best performance for the loading zone's particular demand pattern. To evaluate each model's performance, both root mean square error and mean absolute error are computed. The results show that, for different loading zone demand patterns, different models are better suited. As the prediction horizon increases, predicting further into the future, the neural network approaches start to give better predictions than linear models.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
Nyckelord
- machine learning (artificial intelligence)
- intelligent transportation systems
- data and data science
- urban freight transportation
- information systems and technology
- freight systems
- artificial intelligence and advanced computing applications
- freight transportation data
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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