Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Hangzhou, China

Research Article

Data Classification Model of Improved Swarm Intelligence Algorithm Based on Big Data

Download234 downloads
  • @INPROCEEDINGS{10.4108/eai.19-5-2023.2334269,
        author={Dingsheng  Deng},
        title={Data Classification Model of Improved Swarm Intelligence Algorithm Based on Big Data},
        proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China},
        publisher={EAI},
        proceedings_a={ICBBEM},
        year={2023},
        month={7},
        keywords={big data intelligent algorithm data classification ant colony algorithm},
        doi={10.4108/eai.19-5-2023.2334269}
    }
    
  • Dingsheng Deng
    Year: 2023
    Data Classification Model of Improved Swarm Intelligence Algorithm Based on Big Data
    ICBBEM
    EAI
    DOI: 10.4108/eai.19-5-2023.2334269
Dingsheng Deng1,*
  • 1: Sichuan Minzu College
*Contact email: dds0904@scun.edu.cn

Abstract

In the era of massive data, people have an urgent need for technology that can automatically and intelligently transform data into useful knowledge. This demand promotes the rapid development of data mining technology. Data classification has been extensively studied in the fields of artificial intelligence, network finance, pattern recognition, and machine learning, and numerous classification modeling algorithms have been produced. Although data classification has made certain breakthroughs in theory and technology, it still has some problems, including: the accuracy and effectiveness of classification modeling algorithms, and the intelligibility of classification rules. This paper introduces the representative ant colony algorithm (ACA) and particle swarm optimization algorithm (PSOA) in the swarm intelligence algorithm into data classification mining, and proposes a data classification model based on the improved swarm intelligence algorithm of big data.