Investigating the Impact of Weather on Demand Prediction for Bike Sharing System

Walsh, Dawn (2021) Investigating the Impact of Weather on Demand Prediction for Bike Sharing System. Masters thesis, Dublin, National College of Ireland.

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Abstract

Rebalancing a bike sharing system involves removing bikes from oversubscribed stations and putting them into undersubscribed stations in order to satisfy demand. Predicting the number of spaces required depending on day, time and weather is a challenge. This research proposes to investigate the two most prevalent prediction methods in conjunction with weather data to find whether clustering or tree methods provide a better model for improving demand prediction to aid system rebalancing. The previous research on DC Bikes was replicated, in Dublin however weather has much less of an impact on Dublin Bikes usage. Random Forest Classification gave better demand prediction for rebalancing the bike system at a station level and a model that combines the two methods may well be better overall than either individually.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software H Social Sciences > HE Transportation and Communications > Urban Transportation
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Clara Chan
Date Deposited:	15 Dec 2021 11:57
Last Modified:	15 Dec 2021 11:57
URI:	https://norma.ncirl.ie/id/eprint/5234

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