小样本算法在电网气象灾害预警中的应用

Xiang Chen
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引用次数: 0

摘要

气象灾害预警具有建设内容多、覆盖范围广、复杂性高、工程建设工作量大、难度高等特点,本文通过引入气象灾害预警技术和小样本算法,提高气象灾害预警的准确性,解决现有系统只能泛化预测的问题。本文首先研究了建立气象灾害预警和气象灾害预警的方法,然后设计了基于气象灾害预警和小样本算法的需求分析和对比应用。最后通过实例对比分析气象灾害预警分析与小样本算法的对比效果。气象灾害预警技术与小样本算法解决了当前系统无法对构建内容进行对比的问题。实例结果表明,现有预警系统的分析速度明显优于当前的气象预警系统。小样本算法的比对准确率比单一相似度算法高出1.13%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of small sample algorithm and meteorological disaster early warning in power grid
Meteorological disaster early warning has the characteristics of many construction contents, wide coverage, high complexity, and large workload and high difficulty in project construction In this paper, metrological disaster early warning technology and small sample algorithm are introduced to improve the accuracy of metrological disaster early warning, and solve the problems that the existing system can only generalize the prediction, has high false alarm rate and low work efficiency This paper first studies the method of building metrological disaster early warning and metrological disaster early warning, then designs demand analysis and comparative application based on metrological disaster early warning and small sample algorithm, And finally analyzes the effect of comparison between meteorological disaster early warning analysis and small sample algorithm through example comparison The metrological disaster early warning technology and small sample algorithm solve the problem that the current system cannot compare the construction content The results of the example show that the analysis speed of the existing early warning system is obviously better than the current metrological early warning system, and the comparison accuracy of the small sample algorithm is more than 1.13% higher than that of the single similarity algorithm.
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