Stochastic Models In Geosystems PDF Download
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| Author | : Stanislav A. Molchanov |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 496 |
| Release | : 2012-12-06 |
| Genre | : Science |
| ISBN | : 1461385008 |
Download Stochastic Models in Geosystems Book in PDF, ePub and Kindle
This IMA Volume in Mathematics and its Applications STOCHASTIC MODELS IN GEOSYSTEMS is based on the proceedings of a workshop with the same title and was an integral part of the 1993-94 IMA program on "Emerging Applications of Probability." We would like to thank Stanislav A. Molchanov and Wojbor A. Woyczynski for their hard work in organizing this meeting and in edit ing the proceedings. We also take this opportunity to thank the National Science Foundation, the Office of N aval Research, the Army Research Of fice, and the National Security Agency, whose financial support made this workshop possible. A vner Friedman Willard Miller, Jr. v PREFACE A workshop on Stochastic Models in Geosystems was held during the week of May 16, 1994 at the Institute for Mathematics and Its Applica tions at the University of Minnesota. It was part of the Special Year on Emerging Applications of Prob ability program put together by an organiz ing committee chaired by J. Michael Steele. The invited speakers represented a broad interdisciplinary spectrum including mathematics, statistics, physics, geophysics, astrophysics, atmo spheric physics, fluid mechanics, seismology, and oceanography. The com mon underlying theme was stochastic modeling of geophysical phenomena and papers appearing in this volume reflect a number of research directions that are currently pursued in these areas.
| Author | : |
| Publisher | : |
| Total Pages | : 21 |
| Release | : 1994 |
| Genre | : |
| ISBN | : |
Download Emerging Applications of Probability (Stochastic Models in Geosystems). Book in PDF, ePub and Kindle
The workshop was devoted to several of the most active topics in this area and, in particular, covered: Probabilistic models in geophysics including hierarchical models for geophysical structures, homogenization of random elastic media, propagation of seismic waves, statistical methods for estimation of parameters of seismic waves, prediction problems for seismic phenomena and other geophysical fields. Modern probabilistic and statistical methods in oceanography and atmospheric sciences including: probabilistic and statistical mechanical models of large scale ocean circulation, random fields and stochastic partial differential equations techniques, waves in the ocean in presence of random topography and random forcing, random field modeling of salinity, temperature and other physical fields, weak turbulence. Prediction problems. Distribution functions for vorticity, velocity and dissipation rates. Intermittency and structure functions. Singularities in Euler equations and their relation to turbulence. Turbulent cascades and martingales.
| Author | : Timothy C. Coburn |
| Publisher | : AAPG |
| Total Pages | : 406 |
| Release | : 2005-12-10 |
| Genre | : Petroleum |
| ISBN | : 0891817042 |
Download Stochastic Modeling and Geostatistics Book in PDF, ePub and Kindle
| Author | : Peter Imkeller |
| Publisher | : Birkhäuser |
| Total Pages | : 413 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 3034882874 |
Download Stochastic Climate Models Book in PDF, ePub and Kindle
A collection of articles written by mathematicians and physicists, designed to describe the state of the art in climate models with stochastic input. Mathematicians will benefit from a survey of simple models, while physicists will encounter mathematically relevant techniques at work.
| Author | : Robert Adler |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 473 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461224306 |
Download Stochastic Modelling in Physical Oceanography Book in PDF, ePub and Kindle
The study of the ocean is almost as old as the history of mankind itself. When the first seafarers set out in their primitive ships they had to understand, as best they could, tides and currents, eddies and vortices, for lack of understanding often led to loss of live. These primitive oceanographers were, of course, primarily statisticians. They collected what empirical data they could, and passed it down, ini tially by word of mouth, to their descendants. Data collection continued throughout the millenia, and although data bases became larger, more re liable, and better codified, it was not really until surprisingly recently that mankind began to try to understand the physics behind these data, and, shortly afterwards, to attempt to model it. The basic modelling tool of physical oceanography is, today, the partial differential equation. Somehow, we all 'know" that if only we could find the right set of equations, with the right initial and boundary conditions, then we could solve the mysteries of ocean dynamics once and for all.
| Author | : Daniel P. Heyman |
| Publisher | : Courier Corporation |
| Total Pages | : 564 |
| Release | : 2004-01-01 |
| Genre | : Mathematics |
| ISBN | : 9780486432595 |
Download Stochastic Models in Operations Research Book in PDF, ePub and Kindle
This volume of a 2-volume set explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. Explores stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, this graduate-level text emphasizes the practical importance, intellectual stimulation, and mathematical elegance of stochastic models.
| Author | : Professor Gregoire Mariethoz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 376 |
| Release | : 2014-10-16 |
| Genre | : Science |
| ISBN | : 1118662938 |
Download Multiple-point Geostatistics Book in PDF, ePub and Kindle
This book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable reference for students, researchers and practitioners of all areas of the Earth Sciences where forecasting based on spatio-temporal data is performed.
| Author | : Peter Guttorp |
| Publisher | : CRC Press |
| Total Pages | : 388 |
| Release | : 2018-03-29 |
| Genre | : Mathematics |
| ISBN | : 1351413651 |
Download Stochastic Modeling of Scientific Data Book in PDF, ePub and Kindle
Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics.
| Author | : B. R. Bhat |
| Publisher | : New Age International |
| Total Pages | : 412 |
| Release | : 2004 |
| Genre | : Mathematical statistics |
| ISBN | : 9788122412284 |
Download Stochastic Models: Analysis and Applications Book in PDF, ePub and Kindle
The Book Presents A Systematic Exposition Of The Basic Theory And Applications Of Stochastic Models.Emphasising The Modelling Rather Than Mathematical Aspects Of Stochastic Processes, The Book Bridges The Gap Between The Theory And Applications Of These Processes.The Basic Building Blocks Of Model Construction Are Explained In A Step By Step Manner, Starting From The Simplest Model Of Random Walk And Proceeding Gradually To More Complicated Models. Several Examples Are Given Throughout The Text To Illustrate Important Analytical Properties As Well As To Provide Applications.The Book Also Includes A Detailed Chapter On Inference For Stochastic Processes. This Chapter Highlights Some Of The Recent Developments In The Subject And Explains Them Through Illustrative Examples.An Important Feature Of The Book Is The Complements And Problems Section At The End Of Each Chapter Which Presents (I) Additional Properties Of The Model, (Ii) Extensions Of The Model, And (Iii) Applications Of The Model To Different Areas.With All These Features, This Is An Invaluable Text For Post-Graduate Students Of Statistics, Mathematics And Operation Research.
| Author | : Gregory S. Chirikjian |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 397 |
| Release | : 2009-09-02 |
| Genre | : Mathematics |
| ISBN | : 0817648038 |
Download Stochastic Models, Information Theory, and Lie Groups, Volume 1 Book in PDF, ePub and Kindle
This unique two-volume set presents the subjects of stochastic processes, information theory, and Lie groups in a unified setting, thereby building bridges between fields that are rarely studied by the same people. Unlike the many excellent formal treatments available for each of these subjects individually, the emphasis in both of these volumes is on the use of stochastic, geometric, and group-theoretic concepts in the modeling of physical phenomena. Stochastic Models, Information Theory, and Lie Groups will be of interest to advanced undergraduate and graduate students, researchers, and practitioners working in applied mathematics, the physical sciences, and engineering. Extensive exercises and motivating examples make the work suitable as a textbook for use in courses that emphasize applied stochastic processes or differential geometry.
