摘要
随着深度学习等算法技术的突破,人工智能在气象领域中的应用也越来越广泛。文章分析了人工智能技术在观测环境监控、数据质量核查和设备故障监控等业务中的应用场景,并基于百度EasyDL平台创建了雨量筒是否加盖、雨量筒是否有异物及气溶胶观测设备故障监控等模型。结果表明人工智能技术有可能改变现有的装备保障模式,有效提升保障效率和效果。
With the breakthrough of algorithm technology such as deep learning, the application of artificial intelligence in the field of meteorology is also increasingly widespread. The application scenarios of artificial intelligence technology, such as observation environment monitoring, data quality verification and equipment fault monitoring, are analyzed in this paper. Also, based on Baidu EasyDL platform, models such as whether the rain gauge is covered, whether there are foreign matters in the rain gauge are constructed and the models of fault monitoring of aerosol observation equipment are created. The results show that AI technology could change the existing equipment support mode and effectively improve the ensuring efficiency and effect.
作者
涂爱琴
陈庆亮
于帅
张玉洁
TU Aiqin;CHEN Qingliang;YU Shuai;ZHANG Yujie(Key Laboratory of Atmospheric Optics,Anhui Institute of Optics and Fine Mechanics,Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei 230031,China;Science Island Branch of Graduate School,University of Science and Technology of China,Hefei 230026,China;Key Laboratory for Meteorological Disaster Prevention and Mitigation of Shandong,Jinan 250031,China;Ensuring Center of Atmospheric Sounding Technology,Shandong Meteorological Bureau,Jinan 250031,China)
出处
《智能计算机与应用》
2022年第12期187-191,共5页
Intelligent Computer and Applications
基金
山东省气象局面上科研项目(2019sdqxm06,2020sdqxm05,2020sdqxm06)。
关键词
EasyDL
深度学习
气象装备保障
故障监控
图像识别
时序预测
EasyDL
deep learning
meteorological equipment support
fault monitoring
image recognition
time series prediction
