IDEAS home Printed from https://ideas.repec.org/a/oup/ijlctc/v20y2025ip1979-1993..html

The impact of socio-economic–climatic indicators on hydropower production and energy demand correlation using echo state network and quantum-based sand cat swarm optimization algorithm

Author

Listed:
  • Bahao Li
  • Zhimin Wu
  • Ziwen Zhang
  • Yingmin Li
  • Fatemeh Gholinia

Abstract

The correlation between electricity demand and hydropower production regarding global climate change and socio-economic parameters is a complex issue for policymakers. This study suggests an advanced approach to enhance hydropower output within the framework of climate change and socio-economic parameters. It combines the echo state network (ESN) with a quantum-inspired sand cat swarm optimization (SCSO) algorithm, with a focus on climate-resilient electricity demand. The ESN simulates the nonlinear relationship between climate variables, electricity demand, and socio-economic factors. The SCSO algorithm guides the training of ESN, which improves the optimization procedure.

Suggested Citation

  • Bahao Li & Zhimin Wu & Ziwen Zhang & Yingmin Li & Fatemeh Gholinia, 2025. "The impact of socio-economic–climatic indicators on hydropower production and energy demand correlation using echo state network and quantum-based sand cat swarm optimization algorithm," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 1979-1993.
    • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:1979-1993.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/ijlct/ctaf134
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:oup:ijlctc:v:20:y:2025:i::p:1979-1993.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/ijlct .

    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.