多源异质传感器处理与分销网络相遇:简要回顾和潜在方向
1School of Microelectronics (School of Integrated Circuits), Nanjing University of Science and Technology, Nanjing 210094, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
在配送网络 (DN) 中传感器的部署越来越多,产生了大量的多源异构 (MSH) 数据. 本综述探讨了MSH数据分析,以提高DN可靠性和智能电网建设.
科学领域:
- 电气工程 电气工程
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 由电力自动化和物联网驱动的分布网络 (DN) 中传感器部署的增长.
- 从多层网格架构中的传感器获得的多源异质 (MSH) 数据的指数增长.
- 处理大型MSH数据的挑战,用于传统的可靠性评估和调度规划.
研究的目的:
- 审查对DNs的MSH数据分析的技术发展.
- 为了应对识别关键因素和使用MSH数据动态评估DN可靠性的挑战.
- 提出智能,可靠和稳定的下一代DN建设的未来方向.
主要方法:
- 对DNS中的MSH数据现有技术和算法的分析.
- 传统方法与人工智能的整合,以实现计算适应性.
- 专注于MSH数据处理和评估的关键方法.
主要成果:
- 确定了大规模MSH数据的双重影响:增强可靠性评估基础和对传统方法的计算需求.
- 强调了在极端条件下动态评估和预测DN可靠性的紧迫挑战.
- 建议在DNS中对MSH数据分析的未来实际方向.
结论:
- 对于提高DN可靠性和调度规划,MSH数据分析至关重要.
- 将传统方法与人工智能集成为MSH数据处理提供了一个有希望的方法.
- 未来的研究应该专注于解决用于智能电网建设的DN数据的独特特征.
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