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Carbon dioxide capture is an important way to address climate change and achieve carbon neutrality. This project conducts research from four aspects: data acquisition, feature regulation, model training, and optimization control. Through experimental verification, the method proposed in this project can effectively improve carbon capture efficiency in practical applications, reduce energy consumption and operating costs, and has good multi condition stability and adaptability. The research results of this project will provide new ideas for the practical application and popularization of carbon capture technology.

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Research on Optimization and Energy Efficiency Evaluation of Carbon Capture Process Based on Machine Learning Algorithms

  • 会议论文

  • 发表日期：

    2025年

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  • Xiaokai Zhou,
  • Zixiang Xu,
  • Sitong Ren,
  • Cheng Xu,
  • Yishan Wang,
  • Fangang Zeng

摘要

Carbon dioxide capture is an important way to address climate change and achieve carbon neutrality. This project conducts research from four aspects: data acquisition, feature regulation, model training, and optimization control. Through experimental verification, the method proposed in this project can effectively improve carbon capture efficiency in practical applications, reduce energy consumption and operating costs, and has good multi condition stability and adaptability. The research results of this project will provide new ideas for the practical application and popularization of carbon capture technology.