Computation optimization machine learning de mallick subhashis (14 resultados)
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Paperback. Condición: new. Paperback. A textbook applying fundamental seismology theories to the latest computational tools The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances i…n computing technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models. Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data. Volume highlights include: Mathematical foundations and key equations for computational seismologyEssential theories, including wave propagation and elastic wave theoryProcessing, mapping, and interpretation of prestack dataModel-based optimization and artificial intelligence methodsApplications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problemsExercises applying the main concepts of each chapter Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Condición: New. A textbook applying fundamental seismology theories to the latest computational tools The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances in computing… technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models. Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data. Volume highlights include: Mathematical foundations and key equations for computational seismologyEssential theories, including wave propagation and elastic wave theoryProcessing, mapping, and interpretation of prestack dataModel-based optimization and artificial intelligence methodsApplications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problemsExercises applying the main concepts of each chapter.
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Editorial: American Geophysical Union, 2025
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Condición: New. 2025. 1st Edition. paperback. . . . . .
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Paperback. Condición: new. Paperback. A textbook applying fundamental seismology theories to the latest computational tools The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances i…n computing technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models. Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data. Volume highlights include: Mathematical foundations and key equations for computational seismologyEssential theories, including wave propagation and elastic wave theoryProcessing, mapping, and interpretation of prestack dataModel-based optimization and artificial intelligence methodsApplications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problemsExercises applying the main concepts of each chapter Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Editorial: American Geophysical Union, 2025
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Taschenbuch. Condición: Neu. Neuware - A textbook applying fundamental seismology theories to the latest computational tools The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances…in computing technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models. Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data. Volume highlights include: - Mathematical foundations and key equations for computational seismology - Essential theories, including wave propagation and elastic wave theory - Processing, mapping, and interpretation of prestack data - Model-based optimization and artificial intelligence methods - Applications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problems - Exercises applying the main concepts of each chapter.
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Paperback. Condición: New. A textbook applying fundamental seismology theories to the latest computational tools The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances in computing… technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models. Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data. Volume highlights include: Mathematical foundations and key equations for computational seismologyEssential theories, including wave propagation and elastic wave theoryProcessing, mapping, and interpretation of prestack dataModel-based optimization and artificial intelligence methodsApplications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problemsExercises applying the main concepts of each chapter.
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Editorial: John Wiley & Sons Inc, 2025
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Taschenbuch. Condición: Neu. Computation, Optimization, and Machine Learning in Seismology | Subhashis Mallick | Taschenbuch | AGU Advanced Textbooks | Einband - flex.(Paperback) | Englisch | 2025 | John Wiley & Sons Inc | EAN 9781119654469 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[…at]libri[dot]de | Anbieter: preigu.
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Editorial: American Geophysical Union, 2025
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Editorial: John Wiley & Sons Inc, 2025
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Paperback. Condición: new. Paperback. A textbook applying fundamental seismology theories to the latest computational tools The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances i…n computing technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models. Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data. Volume highlights include: Mathematical foundations and key equations for computational seismologyEssential theories, including wave propagation and elastic wave theoryProcessing, mapping, and interpretation of prestack dataModel-based optimization and artificial intelligence methodsApplications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problemsExercises applying the main concepts of each chapter Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
