在智能城市中实时检测物联网异常和入侵数据,使用多代理系统
1Department of Informatics, Mathematics and Electronics, 1 Decembrie 1918 University of Alba Iulia, 510009 Alba Iulia, Romania.
Sensors (Basel, Switzerland)
|January 8, 2025
概括
一个多代理系统通过自动化机器学习任务来简化智能城市物联网数据分析. 专业代理人和专家系统改善了数据预处理,标签和模型发现,以获得更好的学习成果.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
背景情况:
- 智能城市从众多互联设备中生成复杂的物联网数据.
- 分析这些数据在网络流量管理和机器学习方面带来了重大挑战.
研究的目的:
- 为智能城市提供高效物联网数据分析的多代理系统.
- 为了自动化和优化机器学习工作流程,包括数据预处理,标签和模型选择.
主要方法:
- 实现一个多代理系统,用于不同的机器学习任务的专业代理.
- 集成一个专家系统代理来评估发现的机器学习模型.
主要成果:
- 拟议的系统有效地管理物联网数据的各种机器学习步骤.
- 将任务分给专门的代理人和专家评价增强了学习过程.
结论:
- 多代理系统为智能城市环境中复杂的物联网数据分析提供了强大的解决方案.
- 专业代理和专家评估显著提高了机器学习在这个领域的效率和有效性.
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