Show simple item record

dc.contributor.supervisorLeung, Carson K. (Computer Science)en_US
dc.contributor.authorDeng, Deyu
dc.date.accessioned2021-11-17T21:40:29Z
dc.date.available2021-11-17T21:40:29Z
dc.date.copyright2021-09-23
dc.date.issued2021-09en_US
dc.date.submitted2021-09-23T16:17:21Zen_US
dc.identifier.urihttp://hdl.handle.net/1993/36117
dc.description.abstractDespite urbanization benefiting modern society and the people living in the urban city, the limited public resources, especially parking resources, remain a problem. Parking pricing acts as a tool to adjust the available resources. A logical question is: How to use parking pricing to maximize parking resource utilization while optimizing the parking revenue for parking management? In this MSc thesis, I propose an architecture that utilizes available public resources while optimizing revenue with predefined restrictions, especially in the parking management field. More specifically, I first (a) design a data-driven time series based prediction model, and then (b) design a reinforcement learning based dynamic pricing model to incorporate price restrictions. Moreover, I also (c) come up with metrics to evaluate the dynamic pricing model, as well as (d) implement and evaluate the proposed models with real parking data. Evaluation results show the effectiveness and practicality of my predictive analytics architecture for dynamic pricing for parking applications.en_US
dc.rightsopen accessen_US
dc.subjectData miningen_US
dc.subjectTransportation data miningen_US
dc.subjectData scienceen_US
dc.subjectBusiness analyticsen_US
dc.subjectPredictive analyticsen_US
dc.subjectDynamic pricingen_US
dc.titleDynamic pricing for predictive analytics in parkingen_US
dc.typemaster thesisen_US
dc.degree.disciplineComputer Scienceen_US
dc.contributor.examiningcommitteeDomaratzki, Mike (Computer Science)en_US
dc.contributor.examiningcommitteeWang, Xikui (Warren Centre for Actuarial Studies and Research)en_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.noteFebruary 2022en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record