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Título
Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems
Autor(es)
Palabras clave
Bike sharing systems (BSS)
Regression models
Open data
Data visualization
Multi agent systems
Organizations and institutions
Socio-technical systems
Clasificación UNESCO
1203.17 Informática
Fecha de publicación
2018-01-05
Citación
Lozano, Á., De Paz, J., Villarrubia González, G., Iglesia, D., & Bajo, J. (2018). Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems. Applied Sciences, 8(1), 67. MDPI AG. Retrieved from http://dx.doi.org/10.3390/app8010067
Resumen
[EN] This paper proposes a multi agent system that provides visualization and prediction tools for bike sharing systems (BSS). The presented multi-agent system includes an agent that performs data collection and cleaning processes, it is also capable of creating demand forecasting models for each bicycle station. Moreover, the architecture offers API (Application Programming Interface) services and provides a web application for visualization and forecasting. This work aims to make the system generic enough for it to be able to integrate data from different types of bike sharing systems. Thus, in future studies it will be possible to employ the proposed system in different types of bike sharing systems. This article contains a literature review, a section on the process of developing the system and the built-in prediction models. Moreover, a case study which validates the proposed system by implementing it in a public bicycle sharing system in Salamanca, called SalenBici. It also includes an outline of the results and conclusions, a discussion on the challenges encountered in this domain, as well as possibilities for future work.
URI
ISSN
2076-3417
DOI
10.3390/app8010067
Collections
- BISITE. Artículos [290]
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