59,806 research outputs found

    Long short-term memory networks for earthquake detection in Venezuelan regions

    Get PDF
    Reliable earthquake detection and location algorithms are necessary to properly catalog and analyze the continuously growing seismic records. This paper reports the results of applying Long Short-Term Memory (LSTM) networks to single-station three-channel waveforms for P-wave earthquake detection in western and north central regions of Venezuela. Precisely, we apply our technique to study the seismicity along the dextral strike-slip Boconó and La Victoria - San Sebastián faults, with complex tectonics driven by the interactions between the South American and Caribbean plates.Peer ReviewedPostprint (author's final draft

    CHAOTIC SEISMIC SIGNAL MODELING BASED ON NOISE AND EARTHQUAKE ANOMALY DETECTION

    Get PDF
    Since ancient times, people have tried to predict earthquakes using simple perceptions such as animal behavior. The prediction of the time and strength of an earthquake is of primary concern. In this study chaotic signal modeling is used based on noise and detecting anomalies before an earthquake using artificial neural networks (ANNs). Artificial neural networks are efficient tools for solving complex problems such as prediction and identification. In this study, the effective features of chaotic signal model is obtained considering noise and detection of anomalies five minutes before an earthquake occurrence. Neuro-fuzzy classifier and MLP neural network approaches showed acceptable accuracy of 84.6491% and 82.8947%, respectively. Results demonstrate that the proposed method is an effective seismic signal model based on noise and anomaly detection before an earthquake

    Complex earthquake networks: Hierarchical organization and assortative mixing

    Full text link
    To characterize the dynamical features of seismicity as a complex phenomenon, the seismic data is mapped to a growing random graph, which is a small-world scale-free network. Here, hierarchical and mixing properties of such a network are studied. The clustering coefficient is found to exhibit asymptotic power-law decay with respect to connectivity, showing hierarchical organization. This structure is supported by not only main shocks but also small shocks, and may have its origin in the combined effect of vertex fitness and deactivation by stress release at faults. The nearest-neighbor average connectivity and the Pearson correlation coefficient are also calculated. It is found that the earthquake network has assortative mixing. This is a main difference of the earthquake network from the Internet with disassortative mixing. Physical implications of these results are discussed.Comment: 20 pages including 4 figures and 2 table

    Aftershocks in Modern Perspectives: Complex Earthquake Network, Aging, and Non-Markovianity

    Full text link
    The phenomenon of aftershocks is studied in view of science of complexity. In particular, three different concepts are examined: (i) the complex-network representation of seismicity, (ii) the event-event correlations, and (iii) the effects of long-range memory. Regarding (i), it is shown the clustering coefficient of the complex earthquake network exhibits a peculiar behavior at and after main shocks. Regarding (ii), it is found that aftershocks experience aging, and the associated scaling holds. And regarding (iii), the scaling relation to be satisfied by a class of singular Markovian processes is violated, implying the existence of the long-range memory in processes of aftershocks.Comment: 28 pages, 6 figures and 1 table. Acta Geophysica, in pres

    Scale-Free Network of Earthquakes

    Full text link
    The district of southern California and Japan are divided into small cubic cells, each of which is regarded as a vertex of a graph if earthquakes occur therein. Two successive earthquakes define an edge and a loop, which replace the complex fault-fault interaction. In this way, the seismic data are mapped to a random graph. It is discovered that an evolving random graph associated with earthquakes behaves as a scale-free network of the Barabasi-Albert type. The distributions of connectivities in the graphs thus constructed are found to decay as a power law, showing a novel feature of earthquake as a complex critical phenomenon. This result can be interpreted in view of the facts that frequency of earthquakes with large values of moment also decays as a power law (the Gutenberg-Richter law) and aftershocks associated with a mainshock tend to return to the locus of the mainshock, contributing to the large degree of connectivity of the vertex of the mainshock. It is also found that the exponent of the distribution of connectivities is characteristic for a plate under investigation.Comment: 14 pages, 3 figures, substantial modification
    corecore