Title: A novel urban road management system based on data mining

Authors: Guanlin Chen; Jiapeng Shen; Min Li; Min Jiang

Addresses: School of Computer and Computing Science, Zhejiang University City College, Hangzhou, 310015, China; College of Computer Science, Zhejiang University, Hangzhou, 310027, China ' School of Computer and Computing Science, Zhejiang University City College, Hangzhou, 310015, China; College of Computer Science, Zhejiang University, Hangzhou, 310027, China ' School of Computer and Computing Science, Zhejiang University City College, Hangzhou, 310015, China; College of Computer Science, Zhejiang University, Hangzhou, 310027, China ' Ningbo Smart Urban Management Center, Ningbo, 315041, China

Abstract: With the accelerating process of urbanisation in China, new problems and challenges have also emerged in the management of urban roads. In order to apply the data analysis technology to the above problems, we propose a combined forecasting model which can help us to forecast the number of daily cases that will happen in a region over the next few days. Our experimental results show that this model has better predictive ability than other models and can be applied to a variety of situations. What's more, in order to apply the model to real life, we also develop a novel urban road management system (NURMS) which realises some useful functions such as prediction of the number of daily cases, inquiry of daily cases, and statistical analysis of historical data. We believe our work will bring effective data support to the management of urban roads.

Keywords: data mining; support vector regression; SVR; back propagation; BP; ARIMA; urban road management.

DOI: 10.1504/IJISE.2022.122827

International Journal of Industrial and Systems Engineering, 2022 Vol.40 No.4, pp.472 - 483

Received: 07 Aug 2019
Accepted: 29 Apr 2020
Published online: 13 May 2022 *

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