Stochastic Epidemic Type Model for Analyzing Seismic Activity (original) (raw)

Abstract

In statistical seismology, we can use stochastic process to explain random natural phenomena. One area of study in stochastic processes is point process. At a point process, earthquakes are viewed as a collection of random points in a space, where each point represents the time or/and location of an earthquake. In stochastic epidemic type model earthquake occurrence is assumed as an epidemic, i.e. a large earthquake triggers aftershocks at a certain time interval and the impact may extend to a region. By using point process approach, a stochastic model can be presented with its conditional intensity function, that is the probability of earthquake occurrence per time unit. It is expected that the analysis on the conditional intensity function of the epidemic type model provides information about the probability of earthquake occurrence based on its history. We apply the model to analyze seismic activity in Java Island, Indonesia.

Supported by the Ministry of Research, Technology, and Higher Education of the Republic of Indonesia through Grant of Pascadoctor No. 474/UN27.21/PP/2018.

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Authors and Affiliations

  1. Statistics Department, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta, Indonesia
    Hasih Pratiwi & Respatiwulan
  2. Mathematics Department, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta, Indonesia
    Dody Chandra Priambodo
  3. Mathematics Department, Institut Pertanian Bogor, Kampus Damaga, Bogor, Indonesia
    I. Wayan Mangku

Authors

  1. Hasih Pratiwi
  2. Dody Chandra Priambodo
  3. Respatiwulan
  4. I. Wayan Mangku

Corresponding author

Correspondence toHasih Pratiwi .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy
    Osvaldo Gervasi
  2. University of Basilicata, Potenza, Italy
    Beniamino Murgante
  3. Covenant University, Ota, Nigeria
    Sanjay Misra
  4. Saint Petersburg State University, Saint Petersburg, Russia
    Elena Stankova
  5. Polytechnic University of Bari, Bari, Italy
    Carmelo M. Torre
  6. University of Minho, Braga, Portugal
    Ana Maria A.C. Rocha
  7. Monash University, Clayton, Victoria, Australia
    David Taniar
  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan
    Bernady O. Apduhan
  9. Politecnico di Bari, Bari, Italy
    Eufemia Tarantino
  10. Myongji University, Yongin, Korea (Republic of)
    Yeonseung Ryu

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Pratiwi, H., Priambodo, D.C., Respatiwulan, Mangku, I.W. (2018). Stochastic Epidemic Type Model for Analyzing Seismic Activity. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10960. Springer, Cham. https://doi.org/10.1007/978-3-319-95162-1\_49

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