基于改进的决策树算法,用于多层次冗余数据的快速检索方法.
1State Grid Anhui Electric Power Research Institute, Hefei, 230601, China. qimei85274@163.com.
Scientific reports
|August 2, 2025
概括
本研究介绍了一种改进的决策树算法,以有效地检索电网运营中的冗余数据. 新方法提高了复杂的电网资源业务平台的数据检索准确度和速度.
科学领域:
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
- 电气工程 电气工程
背景情况:
- 电网企业管理大量数据,面临冗余数据检索的挑战.
- 传统的决策树方法对于在冗余干扰中准确的数据采集是不够的.
研究的目的:
- 为电网资源业务平台提出一个多层次的冗余数据检索方法.
- 提高电网运营数据采集准确性和效率.
主要方法:
- 开发了一个多层次的数据决策树,使用电网资源业务中间平台数据.
- 应用Akaike信息基于标准的修剪和殖民地算法进行参数优化.
- 实施了一种新的冗余数据检索方法,设计了处理流和歧视机制.
主要成果:
- 改进的决策树算法将多级冗余数据检索精度提高了14%.
- 获得了0.99的F1最大得分,提取时间为4.5秒.
- 证明有效地检索层次冗余数据,包括图像和文本类别.
结论:
- 拟议的方法显著改善了电网系统中的冗余数据检索.
- 优化的决策树模型提供了网格资源数据层次结构的全面表示.
- 该方法为电力行业的复杂数据管理提供了卓越的实际性能.
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