The application of SSH framework in human resource management system design of operators in digital age

In the digital age, the traditional human resource management system cannot satisfy the enterprises’ requirements for human resource management. Currently, more development opportunities have been provided for the traditional human resource management system. However, the traditional human resource management has the problem of information capture and analysis classification, so this research builds a neural network algorithm model under the SSH framework. The model uses the improved long short-term memory neural network to process and classify the information of human resource management, and realizes the processing of human resource management information. The minimum root-mean-square error of the newly constructed algorithm model is 0.18, which is 0.15 smaller than that of the convolutional neural network and 0.06 smaller than that of the genetic neural network. The fitness of the new model is 6.2% higher than that of the convolutional neural network and 2.8% higher than that of the genetic algorithm. The whole model is superior to the traditional neural network algorithm in fit and accuracy, which can solve the problem of human resource management information processing under SSH framework. It provides new perspectives and tools for understanding and solving complex human resource problems, and expands the application of artificial intelligence and deep learning in the field of human resource management.

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Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-08-26
DOI
https://doi.org/10.1177/14727978251371199
Primary Topic
AI and HR Technologies
Type
article
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article

The application of SSH framework in human resource management system design of operators in digital age

Yang Song, Chunyan Ye, Sai Xia
Journal of Computational Methods in Sciences and Engineering
AI and HR Technologies
article

The application of SSH framework in human resource management system design of operators in digital age

Yang Song, Chunyan Ye, Sai Xia
article en

Abstract

In the digital age, the traditional human resource management system cannot satisfy the enterprises’ requirements for human resource management. Currently, more development opportunities have been provided for the traditional human resource management system. However, the traditional human resource management has the problem of information capture and analysis classification, so this research builds a neural network algorithm model under the SSH framework. The model uses the improved long short-term memory neural network to process and classify the information of human resource management, and realizes the processing of human resource management information. The minimum root-mean-square error of the newly constructed algorithm model is 0.18, which is 0.15 smaller than that of the convolutional neural network and 0.06 smaller than that of the genetic neural network. The fitness of the new model is 6.2% higher than that of the convolutional neural network and 2.8% higher than that of the genetic algorithm. The whole model is superior to the traditional neural network algorithm in fit and accuracy, which can solve the problem of human resource management information processing under SSH framework. It provides new perspectives and tools for understanding and solving complex human resource problems, and expands the application of artificial intelligence and deep learning in the field of human resource management.

Journal of Computational Methods in Sciences and Engineering
Anshan Normal University (CN), Yibin University (CN)
Openalex Percentile: Top 74%
AI and HR Technologies
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The application of SSH framework in human resource management system design of operators in digital age — Yang Song, Chunyan Ye, et al. · Journal of Computational Methods in Sciences and Engineering (2025) | TGRS Research Map | TGRS