Generating Rental Data for Car Sharing Relocation Simulations on the Example of Station-Based One-Way Car Sharing

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dc.contributor.authorBrendel, Alfred Benedikt
dc.contributor.authorRockenkamm, Christian
dc.contributor.authorKolbe, Lutz Maria
dc.date.accessioned2016-12-29T00:39:27Z
dc.date.available2016-12-29T00:39:27Z
dc.date.issued2017-01-04
dc.description.abstractDeveloping sophisticated car sharing simulations is a major task to improve car sharing as a sustainable means of transportation, because new \ algorithms for enhancing car sharing efficiency are formulated using them. \ \ Simulations rely on input data, which is often gathered in car sharing systems or artificially generated. Real-world data is often incomplete and biased while artificial data is mostly generated based on initial assumptions. Therefore, developing new ways for generating testing data is an important task for future research. \ \ In this paper, we propose a new approach for generating car sharing data for relocation simulations by utilizing machine learning. Based on real-world data, we could show that a combined methods approach consisting of a Gaussian Mixture Model and two classification trees can generate appropriate artificial testing data.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.188
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41341
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectcar sharing
dc.subjectdata generator
dc.subjectshared vehicle services
dc.subjectsimulation
dc.subjectvehicle relocation
dc.titleGenerating Rental Data for Car Sharing Relocation Simulations on the Example of Station-Based One-Way Car Sharing
dc.typeConference Paper
dc.type.dcmiText

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