Soft-computing modelling of seismicity in the southern Hellenic arc.
IEEE GEOSCI REMOTE S
323 - 327.
This letter investigates the possible coalition of time intervals and patterns in seismic activity during the preparation process of consecutive sizeable seismic events (i.e., MS >= 5.9). During periods of low-level seismic activity, stress processes in the crust accumulate energy at the seismogenic area, while larger seismic events act as a decongesting mechanism that releases considerable amounts of that energy. Monthly mean seismicity rates have been introduced as a tool to monitor this energy management system and to divert this information into an adaptive neuro-fuzzy inference system. The purpose of the neuro-fuzzy model is to identify and to simulate the possible relationship between mean seismicity rates and time intervals among consecutive sizeable earthquakes. Successful training of the neuro-fuzzy model results in a real-time online processing mechanism that is capable of estimating the time interval between the latest and the next forthcoming sizeable seismic event.
|Title:||Soft-computing modelling of seismicity in the southern Hellenic arc|
|Keywords:||earthquake occurrence, long-term earthquake precursors, neural-fuzzy architecture, pattern recognition, prediction, ARTIFICIAL-INTELLIGENCE TECHNIQUES, LARGE EARTHQUAKES, NEURAL-NETWORK, RECORDINGS, PREDICTION, PATTERNS, FAULT, QUIESCENCE, CATALOGS, REGION|
|UCL classification:||UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Maths and Physical Sciences
UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Institute for Risk and Disaster Reduction
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