IDEAS home Printed from https://ideas.repec.org/a/ids/ijetpo/v20y2025i1-2p163-181.html
   My bibliography  Save this article

Hierarchical classification of dynamic carbon emission factors based on improved support vector machine

Author

Listed:
  • Chenghao Xu
  • Baichong Pan
  • Weixian Che

Abstract

In order to solve the problems of low factor coverage and low factor comprehensiveness existing in the traditional hierarchical classification method of carbon emission factors, a hierarchical classification method of dynamic carbon emission factors based on improved support vector machine is proposed. Firstly, collect dynamic carbon emission data and pre-process the data, calculate the contribution of each factor to the change of total carbon emission according to LMDI decomposition method, and determine the weight of each dynamic carbon emission factor. Introduce kernel function into OC-SVM algorithm in improved support vector machine, map dynamic carbon emission factors to high-dimensional space, and update the optimal hyperplane position with disturbance factors to realise hierarchical classification of dynamic carbon emission factors. The experimental results show that the factor coverage rate of the proposed method is above 90%, the highest factor comprehensiveness can reach 95%, and the practical application effect is good.

Suggested Citation

  • Chenghao Xu & Baichong Pan & Weixian Che, 2025. "Hierarchical classification of dynamic carbon emission factors based on improved support vector machine," International Journal of Energy Technology and Policy, Inderscience Enterprises Ltd, vol. 20(1/2), pages 163-181.
    • Handle: RePEc:ids:ijetpo:v:20:y:2025:i:1/2:p:163-181
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=144307
    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:ijetpo:v:20:y:2025:i:1/2:p:163-181. 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=12 .

    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.