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Short-term power load forecasting model based on multi-strategy improved WOA optimized LSTM

Qian Liang

Qian Liang

  • Key Laboratory of Advanced Manufacturing and Automation Technology, Guilin University of TechnologyGuilin, China
  • College of Mechanical and Control Engineering, Guilin University of TechnologyGuilin, China
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Liang, Qian
, 
Wencheng Wang

Wencheng Wang

  • Key Laboratory of Advanced Manufacturing and Automation Technology, Guilin University of TechnologyGuilin, China
  • College of Mechanical and Control Engineering, Guilin University of TechnologyGuilin, China
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Wang, Wencheng
 und 
Yinchao Wang

Yinchao Wang

  • Key Laboratory of Advanced Manufacturing and Automation Technology, Guilin University of TechnologyGuilin, China
  • College of Mechanical and Control Engineering, Guilin University of TechnologyGuilin, China
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Wang, Yinchao
  
26. Feb. 2024
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Online veröffentlicht: 26. Feb. 2024
Eingereicht: 02. Jan. 2024
Akzeptiert: 09. Jan. 2024
DOI: https://doi.org/10.2478/amns-2024-0323
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© 2024 Qian Liang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Liang, Qian
Key Laboratory of Advanced Manufacturing and Automation Technology, Guilin University of TechnologyGuilin, China
College of Mechanical and Control Engineering, Guilin University of TechnologyGuilin, China
Wang, Wencheng
Key Laboratory of Advanced Manufacturing and Automation Technology, Guilin University of TechnologyGuilin, China
College of Mechanical and Control Engineering, Guilin University of TechnologyGuilin, China
Wang, Yinchao
Key Laboratory of Advanced Manufacturing and Automation Technology, Guilin University of TechnologyGuilin, China
College of Mechanical and Control Engineering, Guilin University of TechnologyGuilin, China
Sprache:
Englisch
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1 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Biologie, Biologie, andere, Mathematik, Angewandte Mathematik, Mathematik, Allgemeines, Physik, Physik, andere
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