文章基本信息

标题：MACHINE LEARNING TOOLS IN THE ANALYZE OF A BIKE SHARING SYSTEM
本地全文：下载
作者：Matej Babic ; Cristiano Fragassa ; Dragan Marinkovic 等
期刊名称：International Journal for Quality Research
印刷版ISSN：1800-6450
电子版ISSN：1800-7473
出版年度：2022
卷号：16
期号：2
页码：375-394
DOI：10.24874/IJQR16.02-04
语种：English
出版社：Center for Quality, Faculty of Engineering, University of Kragujevac, Serbia
摘要：Advanced models, based on artificial intelligence and machine learning, are used here to analyze a bike-sharing system. The specific target was to predict the number of rented bikes in the Nova Mesto (Slovenia) public bike share scheme. For this purpose, the topological properties of the transport network were determined and related to the weather conditions. Pajek software was used and the system behavior during a 30-week period was investigated. Open questions were, for instance: how many bikes are shared in different weather conditions? How the network topology impacts the bike sharing system? By providing a reasonable answer to these and similar questions, several accurate ways of modeling the bike sharing system which account for both topological properties and weather conditions, were developed and used for its optimization.
关键词：Transportation Systems Engineering;Bike-Sharing System (PBS);Artificial Intelligence (AI);Machine Learning (ML);Hybrid Intelligent Systems;Weather Conditions