An up-to-date overview of global optimization methods used to formulate and interpret geophysical observations, for researchers, graduate students and professionals.
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Mrinal K. Sen is a professor of geophysics in the Dept. of Geological Sciences and a research professor at the Inst. for Geophysics of the John A. and Katherine G. Jackson School of Geosciences at the U. of Texas at Austin. He worked in the oil industry from 1979 to 1982 and has been employed at the U. of Texas since 1989. Sen's research interests include seismic wave propagation, inverse theory, and computational geophysics. He holds BS and MS degrees in applied geophysics from the Indian School of Mines and a PhD degree in geophysics from the U. of Hawaii at Manoa. He is a member of SEG, AGU, EAGE, SIAM, and the European Academy of Sciences.
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Hardcover. Zustand: Like New. Second Edition. A firm and square hardback with sharp corners and strong joints, just showing a few very minor cosmetic rubs. Hence a non-text page has a small 'damaged' stamp. Despite such this book is actually in nearly new condition and appears unread. Thus the contents are crisp, fresh and tight; no pen-marks. Now offered for sale at a very sensible price. Bestandsnummer des Verkäufers 209586
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Hardcover. Zustand: new. Hardcover. Providing an up-to-date overview of the most popular global optimization methods used in interpreting geophysical observations, this new edition includes a detailed description of the theoretical development underlying each method and a thorough explanation of the design, implementation and limitations of algorithms. New and expanded chapters provide details of recently developed methods, such as the neighborhood algorithm, particle swarm optimization, hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole Earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration. This up-to-date new edition provides an overview of global optimization methods, and includes succinct descriptions of background theory, advanced concepts and examples of geophysical inversion, enabling readers to formulate their own applications. A valuable resource for researchers, graduate students and professionals in geophysics, inverse theory, exploration geoscience and engineering. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781107011908
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Hardback. Zustand: New. Providing an up-to-date overview of the most popular global optimization methods used in interpreting geophysical observations, this new edition includes a detailed description of the theoretical development underlying each method and a thorough explanation of the design, implementation and limitations of algorithms. New and expanded chapters provide details of recently developed methods, such as the neighborhood algorithm, particle swarm optimization, hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole Earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration. Bestandsnummer des Verkäufers LU-9781107011908
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Hardcover. Zustand: new. Hardcover. Providing an up-to-date overview of the most popular global optimization methods used in interpreting geophysical observations, this new edition includes a detailed description of the theoretical development underlying each method and a thorough explanation of the design, implementation and limitations of algorithms. New and expanded chapters provide details of recently developed methods, such as the neighborhood algorithm, particle swarm optimization, hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole Earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration. This up-to-date new edition provides an overview of global optimization methods, and includes succinct descriptions of background theory, advanced concepts and examples of geophysical inversion, enabling readers to formulate their own applications. A valuable resource for researchers, graduate students and professionals in geophysics, inverse theory, exploration geoscience and engineering. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9781107011908
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Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This up-to-date new edition provides an overview of global optimization methods, and includes succinct descriptions of background theory, advanced concepts and examples of geophysical inversion, enabling readers to formulate their own applications. A valuab. Bestandsnummer des Verkäufers 447213369
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Zustand: New. pp. 296 Index 2nd Edition. Bestandsnummer des Verkäufers 2642163642
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