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Real-time usage forecasting for bike-sharing systems: A study on random forest and convolutional neural network applicability

机译：共享单车系统的实时使用预测：随机森林和卷积神经网络适用性研究

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In this paper, we present a system that has been developed to facilitate the collection and use of Bike-Sharing Systems data for research, notably to develop and compare bike usage forecasting algorithms. We collected internal and external data for six different European cities and developed a system providing short and long-term predictions of bikes and slots availabilities for bike-sharing stations in real-time. In order to provide the best predictions, we developed and compared the performances of two types of algorithm; the first one is based on the state-of-the-art Random Forest algorithm and the second one is based on Convolutional Neural Networks. Our study demonstrates their applicability, showing better accuracy for short-term predictions with the Random Forest algorithm and better long-term prediction accuracy with the Convolutional Neural Networks algorithm.

机译：在本文中，我们介绍了一个已开发的系统，以促进自行车共享系统数据的收集和使用以进行研究，尤其是开发和比较自行车使用率预测算法。我们收集了六个欧洲城市的内部和外部数据，并开发了一个系统，该系统可实时提供自行车的短期和长期预测以及共享自行车站的空位可用性。为了提供最佳的预测，我们开发并比较了两种算法的性能。第一个基于最先进的随机森林算法，第二个基于卷积神经网络。我们的研究证明了它们的适用性，使用随机森林算法显示了更好的短期预测准确性，使用卷积神经网络算法显示了更好的长期预测准确性。

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来源
《2017 Intelligent Systems Conference》|2017年|622-631|共10页
会议地点 London(GB)
作者
Simon Ruffieux; Nicolas Spycher; Elena Mugellini; Omar Abou Khaled;
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作者单位

HumanTech Institute, University of Applied Sciences and Arts of Western, Switzerland, Fribourg, Switzerland;

Institute of Computer Science, University of Bern, Bern, Switzerland;

HumanTech Institute, University of applied Sciences and Arts of Western, Switzerland;

HumanTech Institute, University of applied Sciences and Arts of Western, Switzerland;

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原文格式 PDF
正文语种 eng
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关键词
Prediction algorithms; Forecasting; Urban areas; Predictive models; Real-time systems; Convolutional neural networks; Data models;

机译：预测算法;预测;城市区域;预测模型;实时系统;卷积神经网络;数据模型;;

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4. Real-time usage forecasting for bike-sharing systems: A study on random forest and convolutional neural network applicability [C] . Simon Ruffieux, Nicolas Spycher, Elena Mugellini, Intelligent Systems Conference . 2017

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Real-time usage forecasting for bike-sharing systems: A study on random forest and convolutional neural network applicability

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