Feed aggregator

SummaryDue to the extremely destructive characteristics of seismic hazards, and as one of the effective pre-seismic physical signals, abnormal changes in subsurface fluids can provide key precursor information for earthquake prediction. Furthermore, an efficient method for labelling anomalies in seismic monitoring data is urgently needed. Therefore, this paper analyses the change characteristics of subsurface fluid-water level data and proposes an Anomaly Detection Algorithm of Single Variable Time Series Data Based on Dynamic Parameter Tuning (ADSV-DPT) based on three important characteristics (jump, step and steep), which firstly determines the central tendency of the data by calculating the median of the water level data within the initial window, and then utilizes the Median Absolute Deviation (MAD) as a robust dispersion metric to reduce the impact of extreme values on the anomaly detection. The sliding window mechanism is employed to update the median and MAD step by step, thereby ensuring the efficiency and adaptability of the algorithm in processing time series data. Finally, the anomalies in the data are detected by setting dynamic thresholds. A comparison of the anomaly detection efficacy of the proposed ADSV-DPT algorithm with that of three alternative models (namely, K-Nearest Neighbor, KNN; Pruned Exact Linear Time, PELT; and One-Class Support Vector Machine, OC-SVM) was conducted. The experimental results demonstrate that the ADSV-DPT algorithm outperforms the other models in accurately identifying anomalous features. The average precision, recall, and F1-score of the ADSV-DPT algorithm all exceed 85%. The algorithm's capacity for adapting to variations in the data is noteworthy, as is its ability to accurately identify abnormal values that deviate from the established normal range.

The Northwest can expect a widespread increase in days with cloud-to-ground lightning in the years to come, along with heightened wildfire risk, according to projections made with a unique machine-learning approach developed at Washington State University.

Wind alone does not account for all hurricane-related fatalities. Storm surge and rainfall do as well. Yet the current warning system—the Saffir-Simpson Hurricane Wind Scale—measures a storm's strength solely by wind speed.

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s):

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Chen Chen, Jiangnan Li

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Anatoly I. Nikitin, Vadim A. Nikitin, Alexander M. Velichko, Tamara F. Nikitina

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Brinda Banerjee, Priyanka Karmakar, Sudhir Kumar Singh, Dharmaveer Singh, Biswajit Patra, T.P. Singh, Somil Swarnkar

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): L.F. Chernogor, K.P. Garmash, Q. Guo, V.T. Rozumenko, J. Wang, Y.H. Zhdanko, Y. Zheng

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): V. Guhan, A. Dharma Raju, K. Rama Krishna, K. Nagaratna

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): A.C. Umuhire, N. Gopalswamy, J. Uwamahoro

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): I.G. Zakharov, L.F. Chernogor

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): M.A. Sodunke, J.S. Ojo, F.A. Semire, Y.B. Lawal, O.L. Ojo, G.A. Owolabi, A.I. Olateju

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Djamel Benmenine, E. El-Bialy, Djamel Belatrache, Abdelkader Benmenine, S.M. Shalaby

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): C.M. van Hazendonk, L. Baddeley, K.M. Laundal, D.A. Lorentzen

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Ravi Shanker Pathak, Vinay Pathak, Amit Rai

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Salauddin Mohammad, P Vinay Kumar, Syu-Ruei Jhang, M Venkat Ratnam, Gopa Dutta

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Naveen Krishnan, K. Ravi Kumar

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Oleg Troshichev, Alexander Nikolaev

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Masoud Dehvari, Saeed Farzaneh, Ehsan Forootan

Publication date: September 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 274

Author(s): Tamirat Yohannes, Jinhua Yu, Mulualem Abera, Philemon King’uza, Jonah Kazora, Xuyu Zhang