Earthquake Magnitude and Frequency Forecasting in Northeastern Algeria using Time Series Analysis

被引:5
|
作者
Merdasse, Mouna [1 ]
Hamdache, Mohamed [2 ]
Pelaez, Jose A. [3 ]
Henares, Jesus [4 ]
Medkour, Tarek [5 ]
机构
[1] Univ Sci USTHB, Fac Math, Dept Probabil & Stat, Algiers 16111, Algeria
[2] CRAAG, Seismol Survey Dept, Algiers 16032, Algeria
[3] Univ Jaen, Dept Phys, Jaen 23071, Spain
[4] Int Univ La Rioja, La Rioja 26006, Spain
[5] Natl Sch Artificial Intelligence, Dept Intelligent Syst Engn, Algiers 16309, Algeria
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 03期
关键词
earthquake magnitude forecasting; time series analysis; singular spectrum analysis (SSA); autoregressive integrated moving average (ARIMA) model; SINGULAR SPECTRUM ANALYSIS; EL-ASNAM; AFTERSHOCK SEQUENCE; NORTHERN ALGERIA; SEISMIC HAZARD; DYNAMICS; MODELS; SEISMOTECTONICS; PREDICTABILITY; LITHOSPHERE;
D O I
10.3390/app13031566
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
This study uses two different time series forecasting approaches (parametric and non-parametric) to assess a frequency and magnitude forecasting of earthquakes above Mw 4.0 in Northeastern Algeria. The Autoregressive Integrated Moving Average (ARIMA) model encompasses the parametric approach, while the non-parametric method employs the Singular Spectrum Analysis (SSA) approach. The ARIMA and SSA models were then used to train and forecast the annual number of earthquakes and annual maximum magnitude events occurring in Northeastern Algeria between 1910 and 2019, including 287 main events larger than Mw 4.0. The SSA method is used as a forecasting algorithm in this case, and the results are compared to those obtained by the ARIMA model. Based on the root mean square error (RMSE) criterion, the SSA forecasting model appears to be more appropriate than the ARIMA model. The consistency between the observation and the forecast is analyzed using a statistical test in terms of the total number of events, denoted as N-test. As a result, the findings indicate that the annual maximum magnitude in Northeastern Algeria between 2020 and 2030 will range from Mw 4.8 to Mw 5.1, while between four and six events with a magnitude of at least Mw 4.0 will occur annually.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] New Magnitude Proxy for Earthquake Early Warning Based on Initial Time Series and Frequency
    Wang, Yanwei
    Li, Xiaojun
    Li, Li
    Wang, Zifa
    Lan, Jingyan
    SEISMOLOGICAL RESEARCH LETTERS, 2022, 93 (01) : 216 - 225
  • [2] Earthquake Time Series Analysis for Alarm-based Forecasting Models
    Talbi, Abdelhak
    Hamdache, Mohamed
    INTERNATIONAL WORK-CONFERENCE ON TIME SERIES (ITISE 2014), 2014, : 817 - 817
  • [3] Recurrence quantification analysis for detecting dynamical changes in earthquake magnitude time series
    Lin, Min
    Zhao, Gang
    Wang, Gang
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2015, 26 (07):
  • [4] Earthquake Prediction by Using Time Series Analysis
    Lok, Sultan
    Karabatak, Murat
    9TH INTERNATIONAL SYMPOSIUM ON DIGITAL FORENSICS AND SECURITY (ISDFS'21), 2021,
  • [5] Time series forecasting cancers cases in Algeria using double exponential smoothing method
    Talbi, Melissa
    Adjebli, Ahmed
    Tighilet, Karim
    Louardiane, Mustapha
    Messis, Abdelaziz
    RESEARCH JOURNAL OF BIOTECHNOLOGY, 2024, 19 (03):
  • [6] Time series analysis of soil radon in Northern Pakistan: Implications for earthquake forecasting
    Barkat, Adnan
    Ali, Aamir
    Hayat, Umar
    Crowley, Quentin G.
    Rehman, Khaista
    Siddique, Naila
    Haidar, Takreem
    Iqbal, Talat
    APPLIED GEOCHEMISTRY, 2018, 97 : 197 - 208
  • [7] Possible earthquake forecasting in a narrow space-time-magnitude window
    K. Florios
    I. Contopoulos
    G. Tatsis
    V. Christofilakis
    S. Chronopoulos
    C. Repapis
    Vasilis Tritakis
    Earth Science Informatics, 2021, 14 : 349 - 364
  • [8] Possible earthquake forecasting in a narrow space-time-magnitude window
    Florios, K.
    Contopoulos, I
    Tatsis, G.
    Christofilakis, V
    Chronopoulos, S.
    Repapis, C.
    Tritakis, Vasilis
    EARTH SCIENCE INFORMATICS, 2021, 14 (01) : 349 - 364
  • [9] Earthquake magnitude time series: scaling behavior of visibility networks
    Aguilar-San Juan, B.
    Guzman-Vargas, L.
    EUROPEAN PHYSICAL JOURNAL B, 2013, 86 (11):
  • [10] Time series modeling for forecasting the earthquake behavior in Indonesia
    Alam, Mahmudul
    PROCEEDINGS OF THE 5TH IASME/WSEAS INT CONF ON WATER RESOURCES, HYDRAULICS & HYDROLOGY/PROCEEDINGS OF THE 4TH IASME/WSEAS INT CONF ON GEOLOGY AND SEISMOLOGY: WATER AND GEOSCIENCE, 2010, : 174 - 179