Forecasting travel behaviour from crowdsourced data with machine learning based model (CROSBI ID 647898)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Lopez Aguirre, Angel Javier ; Semanjski, Ivana ; Gautama, Sidharta
engleski
Forecasting travel behaviour from crowdsourced data with machine learning based model
Information and communication technologies have become integral part of our everyday lives. It seems as logical consequence that smart city concept is trying to explore the role of integrated information and communication approach in managing city’s assets and in providing better quality of life to its citizens. Provision of better quality of life relies on improved management of city’s systems (e.g., transport system) but also on provision of timely and relevant information to its citizens in order to support them in making more informed decisions. To ensure this, use of forecasting models is needed. In this paper, we develop support vector machine based model with aim to predict future mobility behavior from crowdsourced data. The crowdsourced data are collected based on dedicated smartphone app that tracks mobility behavior. Use of such forecasting model can facilitate management of smart city’s mobility system but also ensures timely provision of relevant pre-travel information to its citizens.
crowdsourceing ; travel behavior ; smart city ; transport planning
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Podaci o prilogu
93-99.
2016.
objavljeno
Podaci o matičnoj publikaciji
Fifth International Conference on Data Analytics
Bhulai, Sandjai ; Semanjski, Ivana
Wilmington (DE): The International Academy, Research and Industry Association (IARIA)
Podaci o skupu
Data Analytics
predavanje
01.01.2016-01.01.2016
Venecija, Italija