The Competitiveness Evaluation of Performing Troupes Using Principal Component Neural Networks
Year: 2025
Type: article
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.
Authors: Zhensen Liang, Yuanzhen Zhao
Institutions: City University of Macau, Xiamen Institute of Technology
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414643124
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