IDEAS home Printed from https://ideas.repec.org/a/ids/ijisen/v40y2022i4p472-483.html
   My bibliography  Save this article

A novel urban road management system based on data mining

Author

Listed:
  • Guanlin Chen
  • Jiapeng Shen
  • Min Li
  • Min Jiang

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.

Suggested Citation

  • Guanlin Chen & Jiapeng Shen & Min Li & Min Jiang, 2022. "A novel urban road management system based on data mining," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 40(4), pages 472-483.
  • Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:472-483
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=122827
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:472-483. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=188 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.