Geo.Engineerings

AutoCAD Civil 3D Essential Training Course [Size: 1.03 GB] ... AutoCAD Civil 3D software is a design and documentation solution for civil engineering that supports building information modeling (BIM) workflows. By learning to use AutoCAD Civil 3D, you can improve project performance, maintain consistent data, follow standard processes, and respond faster to change. This course gets you up and running with AutoCAD Civil 3D. First, instructor Josh Modglin shows how to model a surface, lay out parcels, and design geometry, including the making of horizontal alignments and vertical profiles. Next, Josh demonstrates how to create corridors, cross sections, pipe networks, and pressure networks. Then, he covers working with feature lines and grading objects, and how to share your data. He wraps up by providing an overview of plan production tools.

Topics include: - Navigating the Civil 3D interface - Using point groups and description keys - Importing survey data - Managing figures - Creating and analyzing surfaces - Creating parcels - Working with alignments - Working with profiles and profile views - Working with assemblies and subassemblies - Creating Basic and Advanced Corridors - Using an Intersection Object - Making sample lines, cross sections, and section views - Creating a pipe network - Understanding pressure parts - Creating and editing feature lines - Creating and editing grading objects - Sharing and referencing data.

Luis Ribeiro e Sousa, Eurípedes Vargas Jr., M.M. Fernandes, Roberto Azevedo ... 474 pages - Publisher: CRC Press; 1st edition (May, 2012) ... Language: English - ASIN: B00BEKEZVA by Amazon ...

Since the 1990s five books on ‘Applications of Computational Mechanics in Geotechnical Engineering’ have been published. Innovative Numerical Modelling in Geomechanics is the 6th and final book in this series, and contains papers written by leading experts on computational mechanics. The book treats highly relevant topics in the field of geotechnics, such as environmental geotechnics, open and underground excavations, foundations, embankments and rockfill dams, computational systems and oil geomechanics. Special attention is paid to risk in geotechnical engineering, and to recent developments in applying Bayesian networks and Data Mining techniques. Innovative Numerical Modelling in Geomechanics will be of interest to civil, mining and environmental engineers, as well as to engineering geologists. The book will also be useful for academics and researchers involved in geotechnics.

Machine Learning Classification Algorithms using MatLab [Size: 580 MB] ... This course is designed to cover one of the most interesting areas of machine learning called classification. I will take you step-by-step in this course and will first cover the basics of MATLAB. Following that we will look into the details of how to use different machine learning algorithms using MATLAB. Specifically, we will be looking at the MATLAB toolbox called statistic and machine learning toolbox. We will implement some of the most commonly used classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error Correcting Output Codes and Ensembles. Following that we will be looking at how to cross validate these models and how to evaluate their performances. Intuition into the classification algorithms is also included so that a person with no mathematical background can still comprehend the essential ideas. The following are the course outlines.

Table of Contents: - Segment 1: Instructor and Course Introduction - Segment 2: MATLAB Crash Course - Segment 3: Grabbing and Importing Dataset - Segment 4: K-Nearest Neighbor - Segment 5: Naive Bayes - Segment 6: Decision Trees - Segment 7: Discriminant Analysis - Segment 8: Support Vector Machines - Segment 9: Error Correcting Output Codes - Segment 10: Classification with Ensembles - Segment 11: Validation Methods - Segment 12: Evaluating Performance. This course is really good for a beginner. It will help you to start from the ground up and move on to more complicated areas. You receive knowledge from a Ph.D. in Computer science (machine learning) with over 10 years of teaching and research experience.

Chester I. Duncan Jr. ... 408 pages - Publisher: Springer;  2nd edition (1998) ... Language: English - ISBN-10: 146137474X - ISBN-13: 978-1461374749

Soils and Foundations for Architects and Engineers, Second Edition is a practical guide to the technology of soil mechanics and foundations, and the application of that technology to the design and construction process. This text provides an up-to-date overview of the classification of soils, the design of foundations, and the behavior of soils under load. Particular emphasis has been given to the subject of piles, piers, and caissons, and to the design and details of construction of basement and retaining walls. New to this edition: Expanded coverage of shear strength of soils, settlement analysis, and expansive soil. + Design requirements for prestressed tiebacks, tiedowns, and rock anchors. + Expansion of information on pile driving techniques including the use of the Engineering News Formula. + A table of British-metric conversions. + Many new solved problems and illustrations. In addition to the numerous new improvements, the author also includes: effects of high water tables on architectural and engineering considerations, design of shear keys used in the transfer of lateral earth pressure from a wall to the supporting element, various drainage alternatives to the structural treatment of adjacent footings, and much more. Soils and Foundations for Architects and Engineers, Second Edition can be used in advanced undergraduate and graduate level courses offered in architectural engineering and civil engineering, as well as be used as a reference book by practicing architects, insurance adjusters and attorneys who litigate or adjudicate claims involving soils and foundations.

A. Schofield ... 216 pages - Publisher: Thomas Telford Publishing; (January, 2005) ... Language: English - ISBN-10: 0727729829 - ISBN-13: 978-0727729828 ...

This book describes the developments leading to the Original Cam Clay model, focusing on fundamentals of the shearing of soil. The aim is to lay the groundwork of understanding that should form the basis of geotechnical design, guiding engineers towards the class of behaviour to be expected under different combinations of effective stress and water content. In this book there are a few equations, but simple ones; much greater challenge rests in the arguments put forward regarding soil behaviour and the intellectual effort needed to keep pace with the author.

Learn Neural Networks using Matlab Course [Size: 187 MB] ... MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language developed by MathWorks. Although MATLAB is intended primarily for numerical computing, but by optional toolboxes, using the MuPAD symbolic engine, has access to symbolic computing capabilities too. One of these toolboxes is Neural Network toolbox. This toolbox is free, open source software for simulating models of brain and central nervous system, based on MATLAB computational platform. In these courses you will learn the general principles of Neural Network Toolbox designed in Matlab and you will be able to use this Toolbox efficiently as well.

The list of contents is: - Introduction: in this chapter the Neural Network Toolbox is Defined and introduced. An overview of neural network application is provided and the neural network training process for pattern recognition, function fitting and clustering data in demonstrated. - Neuron models:  A description of the neuron model is provided, including simple neurons, transfer functions, and vector inputs and single and multiple layers neurons are explained. The format of input data structures is very effective in the simulation results of both static and dynamic networks. So this effect is discussed in this chapter too. And finally the incremental and batch training rule is explained. - Perceptron networks: In this chapter the perceptron architecture is shown and it is explained how to create a perceptron in Neural network toolbox. The perceptron learning rule and its training algorithm is discussed and finally the network/Data manager GUI is explained. - Linear filters: in this chapter linear networks and linear system design function is discussed. The tapped delay lines and linear filters are discussed and at the end of the chapter LMS algorithm and linear classification algorithm used for linear filters are explained. - Backpropagation networks: The architecture, simulation, and several high-performance backpropagation training algorithms of backpropagation networks are discussed in this chapter. - Conclusion: in this chapter the memory and speed of different backpropagation training algorithms are illustrated. And at the end of the chapter all these algorithms are compared to help you select the best training algorithm for your problem in hand. - Matlab Software Installation: You are required to install the Matlab Software on your machine, so you can start executing the codes, and examples we work during the course.