MODELING THE SEISMICITY OF CENTRAL IONIAN ISLANDS WITH SEMI-MARKOV MODELS
Abstract
Earthquakes with M ≥ 5.2 that occurred in the area of central Ionian Islands (1911- 2014) are assumed to form a semi-Markov chain, aiming to contribute in the field of seismic hazard assessment. The sojourn times are considered to be geometric or approximated by Pareto distributions. Destination probabilities are examined and the results demonstrate that in many cases these probabilities become higher adequately forecasting the magnitude class of an anticipated earthquake. The geometrically distributed model can also reveal the more probable occurrence time of the next earthquake since for this model the destination probabilities were found to obtain many times their maximum values for the real occurrence time. The successful forecasting as for the occurrence time is 63.75% for all earthquakes and becomes 71.42% for the larger magnitude events (M ≥ 6.0).
Article Details
- How to Cite
-
Pertsinidou, C., Tsaklidis, G., Limnios, N., & Papadimitriou, E. (2016). MODELING THE SEISMICITY OF CENTRAL IONIAN ISLANDS WITH SEMI-MARKOV MODELS. Bulletin of the Geological Society of Greece, 50(3), 1399–1411. https://doi.org/10.12681/bgsg.11853
- Section
- Seismology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution Non-Commercial License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g. post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. Authors are permitted and encouraged to post their work online (preferably in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.