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Research on seismo-ionospheric anomalies using artificial neural network

机译:利用人工神经网络研究电离层异常

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Presently the discovery and research on the disturbances in the ionosphere before earthquake has become increasingly hot research topic. In this paper, the ionospheric occultation data of the COSMIC was used for a detailed study on the ionospheric respond caused by 7.9 magnitude earthquake occurred in Chile on November 14, 2007 and 7.9 magnitude earthquake occurred in Tonga on March 19, 2009. The paper used interpolation techniques of BP neural network, and analyzed the abnormal changes of the F2-layer peak electron density, NmF2 and F2-peak height, hmF2, over the region around the epicenter. The effective experimental results show that NmF2 and hmF2 in ionosphere apparent negative anomaly phenomenon over the region around the epicenter 5 days before the earthquake. The occurrence of these anomalies is most likely from the imminent earthquake.
机译:目前,关于地震前电离层扰动的发现和研究已成为越来越热门的研究课题。本文利用COSMIC的电离层掩星数据对2007年11月14日智利发生的7.9级地震和2009年3月19日在汤加发生的7.9级地震引起的电离层响应进行了详细研究。 BP神经网络的插值技术,并分析了震中周围区域F2层峰值电子密度NmF2和F2峰高hmF2的异常变化。有效的实验结果表明,电离层NmF2和hmF2在震前5天震中附近区域均表现出负异常现象。这些异常的发生最有可能来自即将发生的地震。

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