测绘科学技术学报2017，Vol.34Issue(1)：1-4,4.DOI:10.3969/j.issn.1673-6338.2017.01.001
利用BP神经网络改进电离层短期预报模型
Improved Prediction Model of Ionospheric TECby BP Neural Network
陆建华 1王斌 1胡伍生2
作者信息
- 1. 苏州市测绘院有限责任公司,江苏 苏州 215006
- 2. 东南大学 交通学院,江苏 南京 210018
- 折叠
摘要
Abstract
Total Electron Content (TEC) is one of the most important characteristic parameters of ionosphere,and TEC prediction also is a hot spot in the research for ionosphere.A local real-time polynomial model is established based on the data provided by JS CORS.And the TECs of Nanjing and Suzhou are calculated by using this model,to compare with the prediction effect of time series model and BP neural network fusion model.The result indicates that the fusion model achieves a higher precision in short-term forecast and the accuracy of fusion model is about 20 percent higher than that of the time series model.关键词
电离层/总电子含量/预报/时间序列模型/BP神经网络Key words
ionosphere/total electron content/forecast/time series model/BP neural network分类
天文与地球科学引用本文复制引用
陆建华,王斌,胡伍生..利用BP神经网络改进电离层短期预报模型[J].测绘科学技术学报,2017,34(1):1-4,4.
