Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17–19, 2023, Beijing, China

Research Article

Construction and Application of Investment Value Model for Hydrogen and Fuel Cell Industries Based on Clustering Algorithm

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  • @INPROCEEDINGS{10.4108/eai.17-11-2023.2342712,
        author={Xudong  Li and Qian  Liu},
        title={Construction and Application of Investment Value Model for Hydrogen and Fuel Cell Industries Based on Clustering Algorithm},
        proceedings={Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17--19, 2023, Beijing, China},
        publisher={EAI},
        proceedings_a={ICEMME},
        year={2024},
        month={2},
        keywords={clustering algorithm; industrial investment; industrial clustering; hydrogen energy and fuel cell industry},
        doi={10.4108/eai.17-11-2023.2342712}
    }
    
  • Xudong Li
    Qian Liu
    Year: 2024
    Construction and Application of Investment Value Model for Hydrogen and Fuel Cell Industries Based on Clustering Algorithm
    ICEMME
    EAI
    DOI: 10.4108/eai.17-11-2023.2342712
Xudong Li1,*, Qian Liu1
  • 1: China Auto Information Technology (Tianjin) Co., Ltd
*Contact email: lixudong2019@catarc.ac.cn

Abstract

As one of the pillar industries of the national economy, automobiles have gradually become a hot field pursued by local governments and industrial capital in recent years, driven by technologies such as electrification, intelligence, networking, and low-carbon. At the same time, the automotive industry has the characteristics of wide technological coverage and strong synergy with related industries. Therefore, in order to better develop the automotive industry, it is necessary to not only deeply analyze the development prospects of various technological routes, but also combine various industrial resource elements, fully explore the value of industrial data, and use the cutting-edge theory of data mining to provide more scientific and quantitative investment value evaluation methods and algorithm models for government departments and industrial capital.