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Appl. Sci. 2018, 8(1), 67; doi:10.3390/app8010067

Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems

1
Faculty of Science, University of Salamanca, Plaza de la Merced s/n, 37002 Salamanca, Spain
2
Department of Artificial Intelligence, Polytechnic University of Madrid, Campus Montegancedo s/n, Boadilla del Monte, 28660 Madrid, Spain
*
Author to whom correspondence should be addressed.
Received: 15 December 2017 / Revised: 1 January 2018 / Accepted: 2 January 2018 / Published: 5 January 2018
(This article belongs to the Special Issue Multi-Agent Systems)
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Abstract

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. View Full-Text
Keywords: bike sharing systems (BSS); regression models; open data; data visualization; multi agent systems; organizations and institutions; socio-technical systems bike sharing systems (BSS); regression models; open data; data visualization; multi agent systems; organizations and institutions; socio-technical systems
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lozano, Á.; De Paz, J.F.; Villarrubia González, G.; Iglesia, D.H.D.L.; Bajo, J. Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems. Appl. Sci. 2018, 8, 67.

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