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首页> 外文期刊>Procedia Computer Science >Neural Network Prediction of Daily Relativistic Electrons Fluence in the Outer Radiation Belt of the Earth: Selection of Delay Embedding Method ?
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Neural Network Prediction of Daily Relativistic Electrons Fluence in the Outer Radiation Belt of the Earth: Selection of Delay Embedding Method ?

机译:地球外辐射带中每日相对论电子通量的神经网络预测:延迟嵌入方法的选择

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摘要

Prediction of the time series of relativistic electrons fluence in the outer radiation belt of the Earth encounters problems caused by complexity and non-linearity of the “solar wind – the Earth’s magnetosphere” system. Artificial neural networks are a biologically inspired architecture that is a suitable tool to solve problems of such type. This study considers the dependence of the quality of prediction on the type and depth of delay embedding of input features.
机译:相对论电子注量在地球外部辐射带中的时间序列的预测遇到了由“太阳风-地球磁层”系统的复杂性和非线性引起的问题。人工神经网络是一种受生物学启发的体系结构,是解决此类问题的合适工具。本研究考虑了预测质量对输入特征延迟嵌入的类型和深度的依赖性。

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