计算机应用研究2024，Vol.41Issue(4)：1138-1142,5.DOI:10.19734/j.issn.1001-3695.2023.07.0377
面向降雨预报的雷达回波预测序列外推方法
Research on extrapolation of radar echo prediction sequence for rainfall prediction
摘要
Abstract
The radar echo extrapolation method is widely used in rainfall forecasting.Addressing the issue of insufficient pre-diction accuracy in radar echoes,this paper proposed a deep learning model DIPredRNN based on recurrent neural networks.This model combined long-term temporal and channel information by introducing a dual attention mechanism of space and channel,improved the long-term dependence of time memory.By introducing an interactive framework of hidden states and in-puts,it retained more features and improved the short-term dependence of temporal memory.This model was experimentally compared with classical models and many advanced models on the HKO-7 and Sichuan datasets.The model achieved the best results in comparing multiple indicators such as extrapolated images,MSE,SSIM,CSI-30～50 dbz.The experiment proves that the proposed DIPredRNN network improves the radar echo prediction performance and has advanced performance.关键词
雷达回波外推/深度学习/循环神经网络Key words
radar echo extrapolation/deep learning/recurrent neural network(RNN)分类
信息技术与安全科学引用本文复制引用
罗健文,邹茂扬,杨昊,陈敏,杨康权..面向降雨预报的雷达回波预测序列外推方法[J].计算机应用研究,2024,41(4):1138-1142,5.基金项目
四川省自然科学基金资助项目(2023NSFSC0482) （2023NSFSC0482）
四川省科技计划资助项目(2022YFS0542) （2022YFS0542）
成都信息工程大学科技创新能力提升计划资助项目(KYTD202324) （KYTD202324）
