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在物联网中探索人力资源管理和数据驱动信息安全的预测模型
1College of Economics and Management, Shanxi University, Taiyuan, 030006, Shanxi, China.
Heliyon
|May 3, 2024
概括
物联网 (IoT) 通过将人力资源需求预测准确度提高到90.2%,销售收入预测提高到93.9%,从而提高了企业管理. 这种数据驱动的方法还将通信网络安全风险预测准确度提高到91.21%.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 信息安全 信息安全
背景情况:
- 物联网 (IoT) 加快了经济发展,但挑战了传统的人力资源管理 (HRM),并引入了通信网络安全风险.
- 由于物联网引起的复杂性,现有的企业管理模式难以满足当代需求.
- 数据驱动技术对于解决安全问题和在物联网时代增强人力资源管理至关重要.
研究的目的:
- 提出一个物联网集成模型,用于预测企业的人力资源需求,使用辐射基功能神经网络.
- 评估模型在预测员工数量和销售收入方面的准确性.
- 评估数据驱动模型对无线通信网络安全风险预测的有效性.
主要方法:
- 物联网技术在企业人力资源管理中的应用.
- 辐射基函数神经网络的整合用于预测建模.
- 对人力资源管理和网络安全的预测模型进行实验分析和评估.
主要成果:
- 拟议的模型在五年内实现了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%.
- 无线通信网络安全风险预测模型在四次测试中显示平均准确率为91.21%.
- 在HRM和网络安全应用中,观察到预测准确度的显著改善.
结论:
- 该研究提供了新的数据驱动解决方案,用于人力资源管理和通信网络安全,使用物联网和人工智能.
- 开发的模型提供了更高的准确性,支持企业更好的决策和风险管理.
- 该研究强调了大数据和人工智能在推进传统企业管理和信息安全方面的潜力.
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