Application of small sample algorithm and meteorological disaster early warning in power grid

• Main Author: Chen, Xiangzhou
• Format: Conference Proceeding
• Language: English
• Published: SPIE 15.08.2023
• ISBN: 9781510666610; 1510666613
• ISSN: 0277-786X
• DOI: 10.1117/12.2685703

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.