Research on future-oriented human resource management technology innovation path based on the perspective of intelligent system DOI Open Access
Xin Xing

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract This paper realizes the research on innovation path of human resource management technology by constructing an intelligent system for future management. Establish data source, process data, and explain SSH framework, KNN algorithm, Bayesian network upcoming According to analysis requirements, determine functional module design database system, synthesize corresponding development tools hardware equipment complete system. Comprehensive is provided analyze in this paper. After analyzing, it concluded that both rate checking completeness accuracy, FW-KNN algorithm 0%~4% higher than other control algorithms. In addition, comprehensive check accuracy employee departure prediction 0.97743, percentage users who expressed satisfaction with modules 44.00~58.00%, while more satisfied 21.00~30.00%, general, maintain a satisfactory experience attitude towards

Language: Английский

Research on future-oriented human resource management technology innovation path based on the perspective of intelligent system DOI Open Access
Xin Xing

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract This paper realizes the research on innovation path of human resource management technology by constructing an intelligent system for future management. Establish data source, process data, and explain SSH framework, KNN algorithm, Bayesian network upcoming According to analysis requirements, determine functional module design database system, synthesize corresponding development tools hardware equipment complete system. Comprehensive is provided analyze in this paper. After analyzing, it concluded that both rate checking completeness accuracy, FW-KNN algorithm 0%~4% higher than other control algorithms. In addition, comprehensive check accuracy employee departure prediction 0.97743, percentage users who expressed satisfaction with modules 44.00~58.00%, while more satisfied 21.00~30.00%, general, maintain a satisfactory experience attitude towards

Language: Английский

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