Artificial neural network (NN) is such a model as to imitate the structure and intelligence feature of human brain. It has strong nonlinear mapping function. To introduce NN into the study of earthquake prediction is ...Artificial neural network (NN) is such a model as to imitate the structure and intelligence feature of human brain. It has strong nonlinear mapping function. To introduce NN into the study of earthquake prediction is not only an extension of the application of artificial neural network model but also a new try for precursor observation to serve the earthquake prediction. In this paper, we analyzed the predictability of time series and gave a method of application of artificial neural network in forecasting earthquake precursor chaotic time series. Besides, taking the ground tilt observation of Jiangning and Xuzhou Station, the bulk strain observation of Liyang station as examples, we analyzed and forecasted their time series respectively. It is indicated that the precision of this method can meet the needs of practical task and therefore of great value in the application to the future practical earthquake analysis and prediction.展开更多
准确的电离层闪烁事件预警是空间天气预报的主要任务之一.针对中国低纬地区特高频(ultra high frequency,UHF)频段电离层闪烁事件预警信息需求,基于小数据量,充分利用经验知识和深度学习算法从电离层闪烁发生前的背景电离层参数中筛选...准确的电离层闪烁事件预警是空间天气预报的主要任务之一.针对中国低纬地区特高频(ultra high frequency,UHF)频段电离层闪烁事件预警信息需求,基于小数据量,充分利用经验知识和深度学习算法从电离层闪烁发生前的背景电离层参数中筛选有效的事件发生前兆因子,进而将电离层闪烁事件预报问题转换为观测数据的分类问题,最终基于深度信念网络形成了一种中国低纬地区UHF频段电离层闪烁事件预报新方法.利用该方法分析了多种观测数据组合与UHF频段电离层闪烁事件发生之间的相关性后,首次发现预报地区东侧跨赤道的电子总含量(total electron content,TEC)随纬度变化剖面的时序数据是电离层闪烁事件预报的重要前兆因子之一,对提升预报性能指标有显著帮助.展开更多
文摘Artificial neural network (NN) is such a model as to imitate the structure and intelligence feature of human brain. It has strong nonlinear mapping function. To introduce NN into the study of earthquake prediction is not only an extension of the application of artificial neural network model but also a new try for precursor observation to serve the earthquake prediction. In this paper, we analyzed the predictability of time series and gave a method of application of artificial neural network in forecasting earthquake precursor chaotic time series. Besides, taking the ground tilt observation of Jiangning and Xuzhou Station, the bulk strain observation of Liyang station as examples, we analyzed and forecasted their time series respectively. It is indicated that the precision of this method can meet the needs of practical task and therefore of great value in the application to the future practical earthquake analysis and prediction.
文摘准确的电离层闪烁事件预警是空间天气预报的主要任务之一.针对中国低纬地区特高频(ultra high frequency,UHF)频段电离层闪烁事件预警信息需求,基于小数据量,充分利用经验知识和深度学习算法从电离层闪烁发生前的背景电离层参数中筛选有效的事件发生前兆因子,进而将电离层闪烁事件预报问题转换为观测数据的分类问题,最终基于深度信念网络形成了一种中国低纬地区UHF频段电离层闪烁事件预报新方法.利用该方法分析了多种观测数据组合与UHF频段电离层闪烁事件发生之间的相关性后,首次发现预报地区东侧跨赤道的电子总含量(total electron content,TEC)随纬度变化剖面的时序数据是电离层闪烁事件预报的重要前兆因子之一,对提升预报性能指标有显著帮助.
