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A statistical investigation of pre-earthquake ionospheric TEC anomalies 被引量:6
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作者 Zhu Fuying Wu Yun +1 位作者 Zhou Yiyan Lin Jian 《Geodesy and Geodynamics》 2011年第1期61-65,共5页
Previous researches show that the total electron content (TEC) in the ionospheric exhibits anomalous disturbances a few days or hours prior to earthquakes. The paper used TEC data from Internet GPS Service ( IGS),... Previous researches show that the total electron content (TEC) in the ionospheric exhibits anomalous disturbances a few days or hours prior to earthquakes. The paper used TEC data from Internet GPS Service ( IGS), and examined 50 earthquakes of magnitude Ms ≥ 7.0 during 2007 - 2009 worldwide. The result shows significant anomalous increases and decreases about 7 days prior to 94% of the earthquakes. 展开更多
关键词 EARTHQUAKE Total Electron Content(TEC) statistical investigation ANOMALY
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Swarming Computational Techniques for the Influenza Disease System
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作者 Sakda Noinang Zulqurnain Sabir +5 位作者 Gilder Cieza Altamirano Muhammad Asif Zahoor Raja Manuel Jesús Sànchez-Chero María-Verónica Seminario-Morales Wajaree Weera Thongchai Botmart 《Computers, Materials & Continua》 SCIE EI 2022年第12期4851-4868,共18页
The current study relates to designing a swarming computational paradigm to solve the influenza disease system(IDS).The nonlinear system’s mathematical form depends upon four classes:susceptible individuals,infected ... The current study relates to designing a swarming computational paradigm to solve the influenza disease system(IDS).The nonlinear system’s mathematical form depends upon four classes:susceptible individuals,infected people,recovered individuals and cross-immune people.The solutions of the IDS are provided by using the artificial neural networks(ANNs)together with the swarming computational paradigm-based particle swarmoptimization(PSO)and interior-point scheme(IPA)that are the global and local search approaches.The ANNs-PSO-IPA has never been applied to solve the IDS.Instead a merit function in the sense of mean square error is constructed using the differential form of each class of the IDS and then optimized by the PSOIPA.The correctness and accuracy of the scheme are observed to perform the comparative analysis of the obtained IDS results with the Adams solutions(reference solutions).An absolute error in suitable measures shows the precision of the proposed ANNs procedures and the optimization efficiency of the PSOIPA.Furthermore,the reliability and competence of the proposed computing method are enhanced through the statistical performances. 展开更多
关键词 DISEASE influenza model reference results particle swarm optimization artificial neural networks interior-point scheme statistical investigations
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