Описываются алгоритмы процедур оценивания параметров распределений и проверки гипотез с помощью статистических критериев. Алгоритмы рассматриваются применительно к их машинной реализации. 

Для статистиков, экономистов и специалистов, использующих методы прикладного статистического анализа 

The book MATLAB Recipes for Earth Sciences is designed to help undergraduate and PhD students, postdocs, and professionals to fi nd quick solutions for common problems in data analysis in earth sciences.

Th e book MATLAB Recipes for Earth Sciences is designed to help undergraduate and postgraduate students, doctoral students, post-doctoral researchers, and professionals fi nd quick solutions for common data analysis problems in earth sciences. It provides a minimal amount of theoretical background and demonstrates the application of all described methods through the use of examples.

Behold the power of the microcomputer before your very eyes! This book took less than a year to complete from the initial conversations between Dan Merriam and myself to final typeset copy. This would have been impossible when the first volume of this book was published. All of the papers in this volume, with one exception, arrived on floppy disk but in four different disk formats and many wordprocessing formats. These were all handled elegantly by our typesetter and converted into the appropriate Macintosh file format. Even some of the figures were placed in the book electronically. I see this as a great boon to the world of science because of the much shorter time between inception and dispersal of scientific knowledge. As a result of using microcomputers to typeset this book, the information contained in it is current and fresh. <...>

Geostatistics is a subset of statistics specialized in analysis and interpretation of geographically referenced data (Goovaerts, 1997; Webster and Oliver, 2001; Nielsen and Wendroth, 2003). In other words, geostatistics comprises statistical techniques that are adjusted to spatial data. Typical questions of interest to a geostatistician are:

how does a variable vary in space?

what controls its variation in space?

where to locate samples to describe its spatial variability?

how many samples are needed to represent its spatial variability?

what is a value of a variable at some new location?

what is the uncertainty of the estimate?

Nowadays, many surficial mineral deposits are being mined out, leaving only deep-seated mineral deposits for feeding raw materials into the industry. Therefore techniques applied to mineral exploration need to be revisited for discovering new mineral resources, which may be located in harsh and remote regions. Over the past decades, remote sensing technology and geographic information system (GIS) techniques have been incorporated into several mineral exploration projects worldwide. This aim is to bridge the knowledge gap for the geospatial-based discovery of buried, covered, and blind mineral deposits. This book details the main aspects of the state-of-the-art remote sensing imagery, geochemical data, geophysical data, geological data, and geospatial toolbox required to explore ore deposits. It covers advances in remote sensing data processing algorithms, geochemical data analysis, geophysical data analysis, and machine learning algorithms in mineral exploration. It also presents approaches on recent remote sensing and GIS-based mineral prospectivity modeling, which offer a piece of excellent information to professional earth scientists, researchers, mineral exploration communities, and mining companies <...>

Освещены общие вопросы геоинформатики, функциональные возможности горно-геологической информационной системы Micromine, основные технологические приемы создания объемных цифровых моделей геологических тел в процессе разведки месторождений полезных ископаемых.

Предназначено для студентов специальности 210502 «Прикладная геология» специализации «Геологическая съемка, поиски и разведка месторождений твердых полезных ископаемых», для специалистов геологоразведочных организаций

Proceedings of the 14th international conference of international association for computer methods and recent advances in geomechanics, Kyoto, Japan, 22–25 september 2014

Over the last half a century, constitutive models for geomaterials and numerical analysis methods have been well developed. Nowadays, numerical methods play a very important role in Geotechnical Engineering. The first pioneering conference was held at Waterways Experiment Station, Vicksburg, Mississippi, USA in 1972 under the leadership of Prof. C.S. Desai. Then, subsequent conferences were held in Blacksburg (USA) – 1976, Aachen (Germany) – 1979, Edmonton (Canada) – 1982, Nagoya (Japan) – 1985, Innsbruck (Austria) – 1988, Cairns (Australia) – 1991, Morgantown (USA) – 1994, Wuhan (China) – 1997, Tucson (USA) – 2001, Torino (Italy) – 2005, and Goa (India) – 2008. Now the conference is organized by IACMAG every three years. The last one, the 13th International Conference on Computer Methods and Advances in Geomechanics, was held in Melbourne, Australia in 2011. The 14th conference, here in Kyoto, was accepted at the Melbourne conference in 2011. This conference series is the main activity of the International Association for Computer Methods and Advances in Geomechanics founded in 70’s by Prof. C.S. Desai of the University of Arizona; the present president of IACMAG is Prof. J. Carter of the University of Newcastle. <...>

The engineer designing such soil structures as embankments, dams, or building foundations should be able to predict the safety of these against collapse or excessive deformation under various loading conditions which are deemed possible. On occasion, he may have to apply his predictive knowledge to events in natural soil or rock outcrops, subject perhaps to new, man-made conditions. Typical of this is the disastrous collapse of the mountain (Mount Toc) bounding the Vajont reservoir which occurred on 9 October 1963 in Italy (Müller 1965). Figure 1.1 shows both a sketch indicating the extent of the failure and a diagram indicating the cross section of the encountered ground movement. <...>

In his foreword to "Soft Computing for Reservoir Characterization and Modeling", Dr. Bertrand Braunschweig posed the question: "What's next?". In this companion volume, the authors have provided an imaginative and comprehensive answer. They have extended the application of soft computing techniques to methodologies used for oil exploration in general and have indicated how these increasingly popular methodologies can be integrated with our more traditional industry techniques. In this collection of articles you will find contributions from largely diverse disciplines, ranging from geostatistics and time lapse seismic to biostratigraphy and core analysis. <...>