Download or read book Discrimination of Seismic Events Using Finnish Station Network written by Timo Tiira and published by . This book was released on 1998 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Seismic Event Discrimination Using Neural Networks written by Joseph E. Bitto and published by . This book was released on 1989 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forensic Explosion Seismology written by So Gu Kim and published by Cambridge Scholars Publishing. This book was released on 2020-03-02 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses three major physical phenomena for active source seismology, namely underwater explosions, underground nuclear explosions, and large-scale on-surface chemical explosions. In particular, contributors consider how to use the technologies and applications in active source seismology and seismo-acoustics, rather than the theoretical approach for the resolution of the forensic explosion seismology in the light of an application for defense sciences. The volume also presents seismological investigations of discrimination between earthquakes and man-made explosions.

Download or read book Data to Test and Evaluate the Performance of Neural Network Architectures for Seismic Signal Discrimination Data Sets 2 3 Volume 1 written by and published by . This book was released on 1992 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study describes a data set that was developed to test and evaluate the performance of neural networks for automated processing and interpretation of regional seismic data. This data set may also be valuable for other applications related to seismic monitoring at regional distances, and it is available at the Center for Seismic Studies (CSS) in an Oracle database or in UNIX tar format on exabyte tapes. It consists of waveform and parametric data from>500 regional events recorded by the short-period elements of the NORESS and ARCESS arrays in Norway, and the GERESS array in Germany (the Oracle database at CSS also included data from the FINESA array in Finland and a 3- component station in Poland called KSP). The epicentral distances are primarily 50-2000 km, and the magnitudes are primarily 1.0-5.0. Most of the events are mining explosions in the western part of the CIS, Sweden, Finland, Poland, and Germany. Also included are 22 presumed underwater explosions, and 51 earthquakes in Fennoscandia that were identified in a regional bulletin produced by the University of Helsinki. Other presumed earthquakes (for which independent bulletin information was not available) include events in the Alps and Mediterranean region that were recorded by GERESS. The Oracle database is in CSS 3.0 format, and the exabyte tapes include waveforms in SAC binary format and parametric data in ASCII tables. Detailed documentation has been developed for each event, and is included in a 13-volume report at the CSS.

Download or read book Machine Learning for Data Science Handbook written by Lior Rokach and published by Springer Nature. This book was released on 2023-08-17 with total page 975 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Download or read book Test and Evaluation of Neural Network Applications for Seismic Signal Discrimination written by and published by . This book was released on 1992 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study describes operational test and evaluation of two neural network applications that were integrated into the Intelligent Monitoring System (IMS) for automated processing and interpretation of regional seismic data. Also reported is the result of a preliminary study on the application of neural networks to regional seismic event identification. The first application is for initial identification of seismic phases (P or S) recorded by 3-component stations based on polarization data and context. This neural network performed 3-6% better than the current rule-based system when tested on data obtained from the 3-component IRIS stations in the former Soviet Union. This resulted in an improved event bulletin which showed that the number of analyst-verified events that were missed by the automated processing decreased by more than a factor of 2 (about 10 events/week). The second operational test was conducted on the neural network developed by MIT/Lincoln Laboratory for regional final phase identification (e.g., Pn, Pg, Sn, Lg, and Rg). This neural network performed 3. 3% better than the rule-based system in IMS station processing. However, for the final phase identifications obtained after network processing (where data from all stations are combined), the gain dropped to about 1.0%. It is likely that this could be regained by using the neural network phase identification confidence factors in the network processing. Finally, our preliminary study on the application of neural networks to identify regional seismic events on the basis of coda shape gave about 80% accuracy on data recorded at GERESS. In general, the neural network classifier utilized the coda decay rate which was lower for the earthquakes than it was for the explosions, although there was substantial overlap.

Download or read book Discrimination of Earthquakes and Chemical Explosions with a Regional Network written by Peder Johansson and published by . This book was released on 1987 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Monitoring the Comprehensive Nuclear Test Ban Treaty Seismic Event Discrimination and Identification written by William R. Walter and published by Springer. This book was released on 2013-04-18 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: In September 1996, the United Nations General Assembly adopted the Comprehensive Nuclear-Test-Ban Treaty (CTBT), prohibiting nuclear explosions worldwide, in all environments. The treaty calls for a global verification system, including a network of 321 monitoring stations distributed around the globe, a data communications network, an international data center, and onsite inspections, to verify compliance. The problem of identifying small-magnitude banned nuclear tests and discriminating between such tests and the background of earthquakes and mining-related seismic events, is a challenging research problem. Because they emphasize CTBT verification research, the 12 papers in this special volume primarily addresses regional data recorded by a variety of arrays, broadband stations, and temporarily deployed stations. Nuclear explosions, earthquakes, mining-related explosions, mine collapses, single-charge and ripple-fired chemical explosions from Europe, Asia, North Africa, and North America are all studied. While the primary emphasis is on short-period, body-wave discriminants and associated source and path corrections, research that focuses on long-period data recorded at regional and teleseismic distances is also presented Hence, these papers demonstrate how event identification research in support of CTBT monitoring has expanded in recent years to include a wide variety of event types, data types, geographic regions and statistical techniques.

Download or read book Application of a Recurrent Neural Network to Seismic Event Discrimination written by Steven Craig Sandven and published by . This book was released on 1991 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Discrimination of Seismic Sources Using Israel Seismic Network written by and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We addressed the problem of automated event discrimination in both the local and teleseismic ranges using the Israel Seismic Network, as an example of a dense regional seismic network. A new high resolution technique was developed, based on multistation representation of the seismic signal: spectral semblance, measuring coherency of spectral shapes, and velogram, characterizing kinematic features. Semblance and energy spectral ratio statistics, applied to a wide variety of local and teleseismic events, showed, for specific spectral bands, almost total separation of explosions and earthquakes. Efficient automated classifiers based on combinations of different physical features of the events have been designed. The discrimination results for the teleseismic data were compared for the ISN and NORESS, showing almost equivalent performance. Noise recordings and teleseismic signals were used to evaluate the ISN detectability by array technique, including adaptive beamforming, optimal detectors, maximum likelihood estimators and phase correlation analysis, applied to the ISN subnetworks with promising results. Experimental relationships between charge weight and magnitude for local single quarry shots and underwater Dead Sea explosions with outstanding high coupling were developed, providing a basis for the execution of effective calibration explosions currently lacking in the region.

Download or read book Seismic Discrimination Using Neural Networks written by Sean F. Walden and published by . This book was released on 1992 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Statistical Discrimination Experiment for Eurasian Events Using a Twenty Seven Station Network written by D. W. Rivers and published by . This book was released on 1980 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: An experiment was performed to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment consisted of digital recordings made at twenty-seven stations, including four large arrays, of one hundred thirty-three Eurasian events. Spectral magnitudes were measured in three frequency bands of the six phases P, Lg, long-period P, long-period S, LR, and LQ. Complexities of the P-waves were measured in three time windows, and corner frequencies and low-frequency spectral levels were computed for the P-wave spectra. When signals could not be detected, spectral magnitudes were measured of noise samples, and these were taken to be detection thresholds. Signal magnitudes and detection thresholds from all the stations were used to find maximum-likelihood estimates of the spectral magnitudes for each event. On account of gaps in the data, many different combinations of different numbers of variables were used in the classification of the one hundred thirty-three events. The variables which were applicable to the most events were short-period P-wave spectral ratios. The most effective discriminants were spectral ratios of Love waves to P waves.

Download or read book Seismic Discrimination written by and published by . This book was released on 1976 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Application of Neural Networks to Seismic Signal Discrimination Research Findings written by James A. Cercone and published by . This book was released on 1994 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research focused on identification and collection of a suitable database, identification of parametric representation of the time series seismic waveforms, and the training and testing of neural networks for seismic event classification. It was necessary to utilize seismic events that had a high degree of reliability for accurate training of the neural networks. The seismic waveforms were obtained from the Center for Seismic Studies and were organized into smaller databases for training and classification purposes. Unprocessed seismograms were not well suited for presentation to a neural network because of the large number of data points required to represent a seismic event in the time domain. The parametric representation of the seismic events in some cases provided adequate information for accurate event classification, while significantly reducing the minimum size of the neural network. Various networks have achieved classification rates ranging from 88 percent classification of three class problem to 75 percent for the 5 class problem. The results vary dependent on the number of classes and the method of parametric transformations utilized. Multiple tests were performed in order to statistically average the training and classification rates. Test summaries presented and individual test results are given in the appendix.

Download or read book Fractal Approach to the Regional Seismic Event Discrimination Problem written by D. N. Belyashov and published by . This book was released on 2000 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the framework of the Comprehensive Test Ban Treaty, development of reliable methods to discriminate between underground nuclear explosions and earthquakes at regional distances (less than 2500km) continues to be very important especially in connection with the last (in May, 1998) nuclear explosions conducted at Indian and Pakistan test sites. Since the lithosphere is a fractal, we suppose the signals, which propagate through the media, inherit its self similar' (scaling) features. We assumed that these features of explosions and earthquakes or their topological reconstructions (embeddings) have to be different. Scaling reflects correlations of more high order then it is possible to estimate by linear discriminating methods and can be used as base of non-linear discrimination. We propose to build a universal geometrical model of a seismic signal using the canon algorithm of F. Takens and to estimate scaling of the model. The scaling features were used as patterns of seismic signals for entering them into an artificial neural network. Records of nuclear explosions and earthquakes from different regions were included into the training set. The net was trained to classify types of seismic events. Results have shown 80% correct classification of the unknown signals. As additional tools for distinguishing between nuclear explosions and earthquakes we propose to use Hurst's method and the cross correlation method. Results of using these methods are demonstrated on examples of some explosions and earthquakes.

Download or read book Application of Neutral Networks to Seismic Signal Discrimination written by and published by . This book was released on 1993 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first Annual Technical Summary of the West Virginia Institute of Technology Applications of Neural Networks to Seismic Classification project. The first year of research focused on identification and collection of a suitable database, identification of parametric representation of the time series seismic waveforms, and the initial training and testing of neural networks for seismic event classification. It was necessary to utilize seismic events that had a high degree of reliability for accurate training of the neural networks. The seismic waveforms were obtained from the Center for Seismic Studies and were organized into three smaller databases for training and classification purposes. Unprocessed seismograms are not well suited for presentation to a neural network because of the large number of data points required to represent a seismic event in the time domain. Parametric representation of the seismic waveform numerically extracts those features of the waveform that enable accurate event classification. Sonograms and moment feature extraction are two of the several transformations investigated for parametric representation of a seismic event. This parametric representation of the seismic events provides adequate information. Neural networks, Data points, Signal discrimination, Parametric representation, Seismic events.

Download or read book Regional Seismic Discrimination in the Baltic Shield Using Network Data written by Peder Johansson and published by . This book was released on 1987 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: