The Competitiveness Evaluation of Performing Troupes Using Principal Component Neural Networks

With the increasing attention paid to network security issues, various industries have become more and more concerned about the security of network environments. Performing arts troupes have also been affected, and the evaluation of their competitiveness has become a crucial research area. In this paper, the authors adopted the principal component neural network technology and selected five performing arts troupes (A, B, C, D, and E) as research objects. They evaluated the competitiveness of performing arts troupes by constructing a competitiveness evaluation system. The authors formed a complete competitiveness evaluation system by combining neural networks, clustering algorithms, and principal component analysis. They successfully analyzed competitiveness of the five performing arts troupes using Statistical Product and Service Solutions software and obtained four principal components of competitiveness evaluation. They found that the higher the score of these four principal components was, the stronger the competitiveness of the troupes was.

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Publication Details

Journal
International Journal of Information Technologies and Systems Approach
Published
2025-09-30
DOI
https://doi.org/10.4018/ijitsa.389921
Primary Topic
Human Motion and Animation
Type
article
Field-Weighted Citation Impact
0.00
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article

The Competitiveness Evaluation of Performing Troupes Using Principal Component Neural Networks

Zhipeng Liang, Y.T. Zhao
International Journal of Information Technologies and Systems Approach
Human Motion and Animation
article

The Competitiveness Evaluation of Performing Troupes Using Principal Component Neural Networks

Zhipeng Liang, Y.T. Zhao
article en

Abstract

With the increasing attention paid to network security issues, various industries have become more and more concerned about the security of network environments. Performing arts troupes have also been affected, and the evaluation of their competitiveness has become a crucial research area. In this paper, the authors adopted the principal component neural network technology and selected five performing arts troupes (A, B, C, D, and E) as research objects. They evaluated the competitiveness of performing arts troupes by constructing a competitiveness evaluation system. The authors formed a complete competitiveness evaluation system by combining neural networks, clustering algorithms, and principal component analysis. They successfully analyzed competitiveness of the five performing arts troupes using Statistical Product and Service Solutions software and obtained four principal components of competitiveness evaluation. They found that the higher the score of these four principal components was, the stronger the competitiveness of the troupes was.

International Journal of Information Technologies and Systems ApproachVol. 18(1)
City University of Macau (MO), Xiamen University of Technology (CN)
Openalex Percentile: Top 66%
Human Motion and Animation
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