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Furnace Temperature Prediction Based on Optimized Kernel Extreme Learning Machine

In: Reconstruction and Intelligent Control for Power Plant

Author

Listed:
  • Chen Peng

    (Shanghai University, School of Mechatronic Engineering and Automation)

  • Chuanliang Cheng

    (Shanghai University, School of Mechatronic Engineering and Automation)

  • Ling Wang

    (Shanghai University, School of Mechatronic Engineering and Automation)

Abstract

In power plants, theFurnace furnace temperature directly affects the combustion efficiency and safe operation of the boiler combustion system, which is of great significance for the boiler combustion control system [1]. However, furnaceFurnace combustion is an extremely complex process, and its temperature is affected by many related factors.

Suggested Citation

  • Chen Peng & Chuanliang Cheng & Ling Wang, 2023. "Furnace Temperature Prediction Based on Optimized Kernel Extreme Learning Machine," Springer Books, in: Reconstruction and Intelligent Control for Power Plant, chapter 0, pages 91-111, Springer.
    • Handle: RePEc:spr:sprchp:978-981-19-5574-7_5
    DOI: 10.1007/978-981-19-5574-7_5
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