Tehnički vjesnik, Vol. 31 No. 3, 2024.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20231205001174
Research on Adaptive Intelligent Decision Algorithm in Industry 4.0 Digital Economy and Management Transformation Based on Clustering Algorithm
Yanzhi Zhang
; College of Technology and Data, Yantai Nanshan University, Yantai, 265713, China
Guoping Zhuang
; Fushan No.1 Senior High, Yantai, 265599, China
Haiyang Lv
; College of Technology and Data, Yantai Nanshan University, Yantai, 265713, China
Qinghua Li
; College of Economics and Management, Yantai Nanshan University, Yantai, 265713, China
Sažetak
How to transform the business model of enterprises and make it more in line with the new requirements of industrial upgrading is an important part of the government's supply-side reform in the era of Industry 4.0. For the current research on the good management transformation of digital economy in the fourth Industrial revolution, linear function and four commonly used nonlinear function models are first selected to test the good management transformation of digital economy in different technologies, and the key success factors of the strategic transformation from traditional industry to Industry 4.0 business model are explored based on fuzzy hierarchical analysis. Logistic and Gompertz models were used to judge the life cycle stage of the hot technologies of the fourth Industrial revolution, and based on their development trend clustering, the hot technology groups of the fourth Industrial revolution were explored. Secondly, k-means clustering algorithm based on the optimal class center perturbation is proposed, and simulation experiments are carried out. A clustering algorithm based on k-means algorithm is designed, and the moving mode of k-means in the algorithm is changed, and a disturbance strategy is added to strengthen the adaptive intelligent decision-making ability of the algorithm. K-means clustering algorithm based on the optimal class center disturbance is proposed, and simulation experiments are conducted. At the same time, the values of step size factors in the algorithm are compared experimentally. Finally, it explores the function mechanism of digital economy, management transformation and management transformation in the operation of supply chain node enterprises. By analyzing the current situation and problems of digital operation of logistics and supply chain enterprises, it constructs the digital operation system of supply chain enterprises, and proposes the path of digital transformation and upgrading of supply chain enterprises, so as to promote the rapid development of supply chain node enterprises.
Ključne riječi
adaptive intelligent decision making; clustering algorithm; digital economy; industry 4.0; management transformation
Hrčak ID:
316370
URI
Datum izdavanja:
23.4.2024.
Posjeta: 46 *