Estimating the Occurrence of Geomagnetic Activity Using the Hilbert‐Huang Transform and Extreme Value Theory by Sean Elvidge

Subjects: “…extreme value theory…”
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Climatological Statistics of Extreme Geomagnetic Fluctuations With Periods From 1 s to 60 min by N. C. Rogers, J. A. Wild, E. F. Eastoe, J. Hübert

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Extreme Value Analysis of Ground Magnetometer Observations at Valentia Observatory, Ireland by Alexandra Ruth Fogg, C. M. Jackman, J. Malone‐Leigh, P. T. Gallagher, A. W. Smith, M. Lester, M.‐T. Walach, J. E. Waters

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TXtreme: transformer-based extreme value prediction framework for time series forecasting by Hemant Yadav, Amit Thakkar

Subjects: “…Extreme value theory…”
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Extreme Space Weather Impacts on GNSS Timing Signals for Electricity Grid Management by T. Etchells, K. L. Aplin, L. Berthoud, A. Kalavana, A. Larkins

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Modeling of spatial extremes in environmental data science: time to move away from max-stable processes by Raphaël Huser, Thomas Opitz, Jennifer L. Wadsworth

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Estimating 𝐿-Functionals for Heavy-Tailed Distributions and Application by Abdelhakim Necir, Djamel Meraghni

“…In this paper we propose, by means of extreme value theory, alternative estimators for 𝐿-functionals and establish their asymptotic normality. …”
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Stochastic Periodic Solution and Persistence of a Nonautonomous Impulsive System with Nonlinear Self-Interaction by Weili Kong, Yuanfu Shao

“…Firstly, by use of extreme-value theory of quadratic function and constructing suitable functional, we study the existence of periodic Markovian process. …”
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A New Statistical Method for Maximum Power Estimation in CMOS VLSI Circuits by N. E. Evmorfopoulos, J. N. Avaritsiotis

“…The method is based on extreme value theory and allows for the calculation of the upper end point of the probability distribution which is followed by the instantaneous power drawn from the supply bus. …”
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Tail Risk in the Chinese Vegetable Oil Market: Based on the EGAS-EVT Model by Yueqiang Zhang, Guanghui Han, Hui Xie, Zixing Wang

“…This paper uses extreme value theory and exponential generalised autoregressive score models to estimate the tail extremes of financial return series. …”
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Analysis and Simulation of Workspace of Dual-arm Robot by Xie Shengliang, Liu Zuoshi

“…Thirdly,the method of partitioning by angle and the extreme value theory are used to extract the boundary points of the workspace. …”
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On the Reusage of Primary Radio Resources through the Exploitation of the Spatiotemporal Robustness of the MIMO Transmissions by G. A. Medina-Acosta, José A. Delgado-Penín

“…The proposed model makes use of the smallest singular values and the Extreme Value Theory for characterizing the robustness of the MIMO systems, having always the premise of preventing significant degradations in the performance of the primary communications, while at the same time an attractive number of potential opportunities for secondary are intended to be offered. …”
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The Probability of the May 2024 Geomagnetic Superstorm by S. Elvidge, D. R. Themens

“…The widespread visibility of auroras at unusually low latitudes attracted global media attention. Using extreme value theory (EVT), this study estimates the return periods for the May 2024 storm based on several geomagnetic indices. …”
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Estimation of the Solar Wind Extreme Events by C. Larrodera, L. Nikitina, C. Cid

“…Abstract This research provides an analysis of extreme events in the solar wind and in the magnetosphere due to disturbances of the solar wind. Extreme value theory has been applied to a 20‐year data set from the Advanced Composition Explorer spacecraft for the period 1998–2017. …”
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Method based on contrastive incremental learning for fine-grained malicious traffic classification by Yifeng WANG, Yuanbo GUO, Qingli CHEN, Chen FANG, Renhao LIN, Yongliang ZHOU, Jiali MA

“…In order to protect against continuously emerging unknown threats, a new method based on contrastive incremental learning for fine-grained malicious traffic classification was proposed.The proposed method was based on variational auto-encoder (VAE) and extreme value theory (EVT), and the high accuracy could be achieved in known, few-shot and unknown malicious classes and new classes were also identified without using a large number of old task samples, which met the demand of storage and time cost in incremental learning scenarios.Specifically, the contrastive learning was integrated into the encoder of VAE, and the A-Softmax was used for known and few-shot malicious traffic classification, EVT and the decoder of VAE were used for unknown malicious traffic recognition, all classes could be recognized without a lot of old samples when learning new tasks by using VAE reconstruction and knowledge distillation methods.Experimental results indicate that the proposed method is efficient in known, few-shot and unknown malicious classes, and has greatly reduced the forgetting speed of old knowledge in incremental learning scenarios.…”
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Workspace Analysis of Hydraulic Follow-up Arm based on Monte Carlo Method by Pengyun Feng, Liangbin Zhan, Yanping Xiao, Tiancheng Huang

“…Based on Monte Carlo method and extreme value theory， the working face at the height of fracturing wellhead is solved， and the influence of the arm length of hydraulic servo arm on the stopping distance and working width is studied under the condition of fixed stopping error. …”
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Data-driven upper bounds and event attribution for unprecedented heatwaves by Mark D. Risser, Likun Zhang, Michael F. Wehner

“…In the aftermath of these devastating events, there is interest in identifying worst-case thresholds or upper bounds that quantify just how hot temperatures can become. Generalized Extreme Value theory provides a data-driven estimate of extreme thresholds; however, upper bounds may be exceeded by future events, which undermines attribution and planning for heatwave impacts. …”
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Bayesian Inference for Solar Flare Extremes by B. Griffiths, L. Fawcett, A. C. Green

“…In this paper we use Extreme Value Theory to model extreme solar flares, with inference performed in the Bayesian paradigm. …”
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Prediction of High-ozone Events Using GAM, SMOTE, and Tail Dependence Approaches in Texas (2005–2019) by Benjamin Brown-Steiner, Xiong Zhou, Matthew J. Alvarado, Brook T. Russell

“…Abstract We test three methods for ozone prediction in the El Paso (ELP) and Houston-Galveston-Brazoria (HGB) regions of Texas from 2005–2019: (1) a Generalized Additive Model (GAMs) approach; (2) a GAM approach with the addition of the Synthetic Minority Over-sampling TEchnique (SMOTE) and (3) a tail dependence modeling approach based in extreme value theory (EVT). We also compare the feature selection capabilities of the tail dependence approach to other feature selection methods. …”
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Extreme Event Statistics in Dst, SYM‐H, and SMR Geomagnetic Indices by A. Bergin, S. C. Chapman, N. W. Watkins, N. R. Moloney, J. W. Gjerloev

“…The Dst index ring‐current monitor, derived from an hourly average over four low‐latitude stations, is a benchmark for extreme space weather events, and has been extensively studied statistically. We apply extreme value theory (EVT) to two geomagnetic ring current indices: SYM‐H (derived from 6 stations) and SMR (derived from up to 120 stations). …”
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