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EN
Is it possible to predict location, time and magnitude of earthquakes through identifying their precursors based on remotely sensed data? Earthquakes are usually preceded by unusual natural incidents that are considered as earthquake precursors. With the recent advances in remote sensing techniques which have made it possible monitoring the earth’s surface with diferent sensors, scientists are now able to better study earthquake precursors. Thus, the present study aims at developing the algorithm of classic PS-InSAR processing for obtaining crustal deformation values at the epicenter of earthquakes with magnitude larger than 5.0 on the Richter scale and with oblique thrust faulting and then after calculating temperature values using remotely sensed thermal imagery at the epicenter of same earthquakes; thermal and crustal deformation anomalies were calculated using data mining techniques before earthquake occurrence. In the next stage, taking the correlation between thermal anomalies and crustal deformation anomalies at the epicenter of the study earthquakes into account, an integrated technique was proposed to predict probable magnitude and time of oblique thrust earthquakes occurrence over the earthquake-prone areas. Eventually, the validity of the proposed algorithm was evaluated for an earthquake with a diferent focal mechanism. The analysis results of the thermal anomalies and crustal deformation anomalies at the epicenter of April 16, 2016, Japan-Kumamoto earthquake of magnitude 7.0 with strike-slip faulting, showed completely diferent trends than the suggested patterns by the proposed algorithm.
EN
Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar’s statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.
EN
The process of stress accumulation near earthquake faults during the aseismic period in between two major seismic events in seismically active regions has become a subject of research during the last few decades. In the present paper a long dip -slip fault is taken to be situated in a viscoelastic layer over a viscoelastic half space representing the lithosphere-asthenosphere system. A movement of the dip-slip nature across the fault occurs when the accumulated stress due to various tectonic reasons, e.g., mantle convection etc., exceeds the local friction and cohesive forces across the fault. The movement is assumed to be slipping in nature, expressions for displacements, stresses and strains are obtained by solving the associated boundary value problem with the help of integral transformation and Green's function method. A detailed study of these expressions may give some ideas about the nature of stress accumulation in the system, which in turn will be helpful in formulating an earthquake prediction programme.
EN
In the previous paper the electric field Einside, inside a conductive path (and along its axis), having a conductivity s appreciably larger than that of the host medium, s', was studied in the static approximation, for the case of a current dipole source parallel to the path. Here, the same problem is studied but for a source perpendicular to the path. The following two types of paths we considered: (i) a cylindrical channel of radius R and infinite length, and (ii) a layer of width w and infinite extent. If D denotes the distance of the source from the path, and d the distance of the measuring site from the source, we find that the electric field Einside at remote sites (e.g., d/R or d/w of the order of 10(2)) varies as 1/D for the case of a source neighboring to the conductive cylinder, while it is almost independent of D (and w) for the case of a layer. In the case of the cylinder, the values of the ratio Einside/Ehost at (d/R)crit (see the previous paper); significantly exceed (e.g., by one order of magnitude for usual conductivity ratios between 200/1 and 4000/1, but for appreciably small values of D/R, e.g., D/R=2) the corresponding values when the dipole is parallel to the path. The general case, when the dipole source forms a certain angle with its neighboring highly conductive path terminating inside the host medium, is also investigated. The following four points emerge as far as the electric field Eoutside measured inside the more resistive medium but close to an edge is concerned. First, its direction is regulated from the angle between the emitting dipole and the direction of the (elongated) conductive path (as well as from the distance of the source). Second, its amplitude is usually larger than that of Ehost by a factor of around s/s', but there arc also some cases of over-amplification, i.e., the value of Eoutside/Ehost significantly exceeds the conductivity ratio s/s': such an over-amplification may even occur in cases of conductive paths that are not connected. Third, its amplitude versus the distance from the edge varies only slowly, i.e., [Eoutside] 1/r(t) where t is around (but smaller than) unity. Fourth, for a circularly polarized EM plane wave incident on the surf ace of a conductive half-space (containing a highly conductive path close to the interface), the direction of the electric field variations, measured on the surface but close to the end of the path, is generally different from the direction of Eoutside arising from a dipole source which forms a certain angle with its neighboring conductive path. Finally, the above points are applied to the case of the low frequency electric signals that are detected before earthquakes; this results in a natural explanation of the procedure that is followed to determine the parameters of an impending earthquake from the components of the precursory electric signal.
EN
Numerical simulations of the dislocation density evolution exhibit some perturbations which may be identified as seismic events. The influences of tidal stresses and random disturbances related to the material heterogeneities are analyzed. In relation to this analysis some problems of earthquake prediction and earthquake precursors are discussed. Occurrences of seismic events are very sensitive to small disturbances, while the great disturbances in tidal influence or in material properties cause the disappearance of the events.
EN
Uyeda in an intuitive study has recently shown that an investigation of the predictions issued for large earthquakes in Greece can give a convincing answer to the question whether or not VAN predictions are to be ascribed to chance. In this paper, we give clarifications concerning some misunderstanding on the VAN predictions (of large earthquakes) issued by VAN during the last decade.
EN
A problem of estimation of the prediction efficiency parameters, namely: the success rate and the alarm rate, under uncertain identification of prediction targets in a test data set is considered. Due to the exponential distribution of earthquake magnitude, the problem is particularly significant in magnitude threshold based earthquake prediction. It has been shown that a proper approach to the problem must take into account the probability of incidental correlation of issued predictions with the "other" events that are not targets of prediction but that are included in the test data. A complete solution for the two-class and multiclass cases is given. Since in the multiclass case the final system of equations is ill-conditioned, an approximate way of estimation of the prediction rates is proposed. Numerical test have proved correctness of the solution and reasonability of the approximation. The same tests show that formerly used estimators can deliver unacceptable results.
EN
One of the possible ways of evaluation of the earthquake prediction efficiency is a posterior count of successful predictions compared with the number of all issued predictions and the number of all events which should be predicted. Two efficiency parameters are in general use: the success rate defined as a percentage of the successful predictions in the total number of issued predictions and the alarm rate defined as a percentage of the total number of issued predictions and the alarm rate defined as a percentage to be successful predictions in the number of events which should be predicted. These parameters cannot be easily assessed when the identification of targets of prediction is incertain. When the prediction system aims at the events of magnitudes not lower than a given threshold value, the uncertainly can be generated by errors in magnitude evaluations. An estimation of the succes and alarm rates under encertain identification of prediction targets is formulates as a probabilistic transition from the actual to observed magnitudes. In general, the problem can be solved only when the probability of incidental correlation of issued predictions with the 'other' events that are not targets of prediction, but that are included a test set, is taken into account. A parameter controlling these incidental correlations, called the incidental correlation rate, is defined as the ratio of the number of incidential correlations to the total number of 'other' events. A complete solution for the two-class and multiclass cases is given. The two-class case, in which an event both actually falls into and ois observed as falling into one of two categories, is solved on the basis of Bayes theorem. In the multiclass case, coresponding to the actual situation in the evaluation of earthquake prediction efficiency, the transition from the actual to observed magnitude classes of events that originally follow the magnitude-frequency relation, is considered. This case is solved by an analysis of the prediction and transition processes, given the prediction and incidental correlation rates and the transition probabilities. Since the final system of equations is strongly ill-conditioned, an approximate way of estimation of the prediction efficiency is proposed. Numerical tests, carried out for various combinations of initial conditions and Monte Carlo simulations of the prediction/transition processes, have proved that the solution is correct and its approximation is reasonable. The same tests show taht the estimators inferred from previous suggestions of several authors can lead to unacceptable results.
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