Introduction to Environmental Data Analysis and Modeling, Moses Eterigho Emetere; Esther Titilayo Akinlabi
Автор: Reddy, J. N. Название: Introduction to the finite element method / ISBN: 1259861902 ISBN-13(EAN): 9781259861901 Издательство: McGraw-Hill Рейтинг: Цена: 38265.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.
An up-to-date, self-contained introduction to the theory and applications of the finite element method
This thoroughly revised classic engineering textbook offers a broad-based overview of the finite element method. Written by a world-renowned mechanical engineering researcher and author, the book shows, step-by-step, how to calculate numerical solutions to steady-state as well as time-dependent problems. You also get detailed problems with worked-out solutions and downloadable programs that can be used and modified for real-world situations. Special attention is paid to applications that are important in bioengineering, fluid and thermal sciences, structural mechanics, and a host of applied sciences.
Introduction to the Finite Element Method, Fourth Edition, covers: - Mathematical preliminaries and classical variational methods - 1-D finite element models of second-order differential equations - Applications to 1-D heat transfer and fluid and solid mechanics problems - Finite element analysis of beams and circular plates - Plane trusses and frames - Eigenvalue and time-dependent problems in 1-D - Numerical integration and computer implementation in 1-D - Single-variable problems in two dimensions - 2-D interpolation functions, numerical integration, and computer implementation in 2-D - Flows of viscous incompressible fluids - Plane elasticity - 3-D finite element analysis
Описание: This book presents an introductory overview of spatial data analysis methods and geoinformation analysis techniques. Each chapter introduces the related theory, explains how to interpret metrics outputs, and provides worked examples using ArcGIS and GeoDa. This is a valuable resource for graduate students and researchers analyzing geospatial data.
Описание: This text presents notions and ideas at the foundations of a statistical treatment of risks. Such knowledge facilitates the understanding of the influence of random phenomena and gives a deeper understanding of the possibilities offered by and algorithms found in certain software packages. Since Bayesian methods are frequently used in this field, a reasonable proportion of the presentation is devoted to such techniques. The text is written with a student in mind who has studied elementary undergraduate courses in engineering mathematics, maybe including a minor course in statistics. Despite employment of the style of presentation traditionally found in the mathematics literature (including descriptions like definitions, examples, etc.). Probability and Risk Analysis emphasizes an understanding of the theory and methods presented; hence, comments are given verbally and a reasoning is frequent. With respect to the contents (and its presentation), the ambition has not been to write just another new textbook on elementary probability and statistics. There are lots of such books, but instead the focus is on applications within the field of risk and safety analysis.
Описание: This book introduces methods of re-processing images to extract numerical information that can be used to quantify the observables in environmental modelling. Experiments or procedures that yield large images can be statistically or parametrically examined. Through the use of open source libraries, the book shows how ‘big data’ in the form of images or datasets can be comparatively analysed along same defined procedures or standards.
This book helps to solve the challenges of discarding datasets that are relevant directly or indirectly to the research. The habit of screening datasets leads to the discard of over 90% of the original dataset or images generated in the experiments or procedure. If the images or datasets are generated under the same principles or conditions, then each measurement may be the narrative of unique events. The focus of this book is to enlighten researchers on how to analyse measurements with the aim of ensuring 100% utilization.
Автор: Ekkehard Holzbecher Название: Environmental Modeling ISBN: 3662500531 ISBN-13(EAN): 9783662500538 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This revised book has two aims: to introduce basic concepts of environmental modelling and to facilitate the application of the concepts using modern numerical tools such as MATLAB. It is targeted at all natural scientists dealing with the environment.
Описание: The Hilbert-Huang Transform (HHT) is a recently developed technique used to analyze nonstationary data. These results are compared to the results from the traditional methods such as those based on Fourier transform and other classical statistical tests.
Описание: This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences.
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