Niu Xuejie
College of Economics and Management, Shanxi University, Taiyuan, 030006, Shanxi, China.
Heliyon. 2024 Apr 15;10(9):e29582. doi: 10.1016/j.heliyon.2024.e29582. eCollection 2024 May 15.
The advent of the Internet of Things (IoT) has accelerated the pace of economic development across all sectors. However, it has also brought significant challenges to traditional human resource management, revealing an increasing number of problems and making it unable to meet the needs of contemporary enterprise management. The IoT has brought numerous conveniences to human society, but it has also led to security issues in communication networks. To ensure the security of these networks, it is necessary to integrate data-driven technologies to address this issue. In response to the current state of human resource management, this paper proposes the application of IoT technology in enterprise human resource management and combines it with radial basis function neural networks to construct a model for predicting enterprise human resource needs. The model was also experimentally analyzed. The results show that under this algorithm, the average prediction accuracy for the number of employees over five years is 90.2 %, and the average prediction accuracy for sales revenue is 93.9 %. These data indicate that the prediction accuracy of the model under this study's algorithm has significantly improved. This paper also conducted evaluation experiments on a wireless communication network security risk prediction model. The average prediction accuracy of four tests is 91.21 %, indicating that the model has high prediction accuracy. By introducing data-driven technology and IoT applications, this study provides new solutions for human resource management and communication network security, promoting technological innovation in the fields of traditional human resource management and information security management. The research not only improves the accuracy of the prediction models but also provides strong support for decision-making and risk management in related fields, demonstrating the great potential of big data and artificial intelligence technology in the future of enterprise management and security.
物联网（IoT）的出现加快了各个行业的经济发展步伐。然而，它也给传统人力资源管理带来了重大挑战，暴露出越来越多的问题，使其无法满足当代企业管理的需求。物联网给人类社会带来了诸多便利，但也引发了通信网络中的安全问题。为确保这些网络的安全，有必要整合数据驱动技术来解决这一问题。针对当前人力资源管理的现状，本文提出将物联网技术应用于企业人力资源管理，并将其与径向基函数神经网络相结合，构建企业人力资源需求预测模型。还对该模型进行了实验分析。结果表明，在该算法下，五年内员工数量的平均预测准确率为90.2%，销售收入的平均预测准确率为93.9%。这些数据表明，本研究算法下模型的预测准确率有了显著提高。本文还对无线通信网络安全风险预测模型进行了评估实验。四次测试的平均预测准确率为91.21%，表明该模型具有较高的预测准确率。通过引入数据驱动技术和物联网应用，本研究为人力资源管理和通信网络安全提供了新的解决方案，推动了传统人力资源管理和信息安全管理领域的技术创新。该研究不仅提高了预测模型的准确性，还为相关领域的决策和风险管理提供了有力支持，展示了大数据和人工智能技术在企业管理和安全未来发展中的巨大潜力。
