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Research on the optimization of intelligent electricity billing consolidation and the expansion of refund services based on deep learning

Author

Listed:
  • Ye Chen
  • Fan Wu
  • Yue Wang
  • Jingyan Shi
  • Kun Wang
  • Bo Zhang

Abstract

The rapidly expanding electrical sector urgently requires more effective strategies for electricity fee management. This article designs and implements an intelligent billing management system based on the service-oriented architecture. Additionally, this research proposes a predictive model based on deep learning that integrates a cascaded model utilizing particle swarm optimization, self-organizing maps, and bidirectional gated recurrent units algorithms to accurately forecast electricity revenue and refund scenarios. Experimental results demonstrate the superior accuracy and efficiency of this integrated model.

Suggested Citation

  • Ye Chen & Fan Wu & Yue Wang & Jingyan Shi & Kun Wang & Bo Zhang, 2025. "Research on the optimization of intelligent electricity billing consolidation and the expansion of refund services based on deep learning," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 9-31.
    • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:9-31.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctae261
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