Download or read book Current Practices and Future Trends in Deep Foundations written by Jerry A. DiMaggio and published by . This book was released on 2004 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: GSP 125 contains 26 papers on state-of-the-art developments in deep foundation collected in honor of George G. Goble, Ph.D., P.E.

Download or read book An Introduction to Deep Reinforcement Learning written by Vincent Francois-Lavet and published by Foundations and Trends (R) in Machine Learning. This book was released on 2018-12-20 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. Deep RL opens up many new applications in domains such as healthcare, robotics, smart grids, finance, and many more. This book provides the reader with a starting point for understanding the topic. Although written at a research level it provides a comprehensive and accessible introduction to deep reinforcement learning models, algorithms and techniques. Particular focus is on the aspects related to generalization and how deep RL can be used for practical applications. Written by recognized experts, this book is an important introduction to Deep Reinforcement Learning for practitioners, researchers and students alike.

Download or read book An Introduction to Deep Foundations written by J. Paul Guyer and published by Independently Published. This book was released on 2018-10 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory technical guidance for civil, structural and geotechnical engineers and construction managers interested in design and construction of deep foundations for buildings and other structures. Here is what is discussed: 1. GENERAL 2. FLOATING FOUNDATIONS 3. SETTLEMENTS OF COMPENSATED FOUNDATIONS 4. UNDERPINNING 5. EXCAVATION PROTECTION 6. DRILLED PIERS 7. FOUNDATION SELECTION CONSIDERATIONS.

Download or read book An Introduction to Deep Foundations written by J. Paul Guyer and published by Guyer Partners. This book was released on 2018-10-01 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory technical guidance for civil, structural and geotechnical engineers and construction managers interested in design and construction of deep foundations for buildings and other structures. Here is what is discussed: 1. GENERAL 2. FLOATING FOUNDATIONS 3. SETTLEMENTS OF COMPENSATED FOUNDATIONS 4. UNDERPINNING 5. EXCAVATION PROTECTION 6. DRILLED PIERS 7. FOUNDATION SELECTION CONSIDERATIONS.

Download or read book Soil Dynamics and Foundation Modeling written by Junbo Jia and published by Springer. This book was released on 2017-11-26 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive topical overview on soil dynamics and foundation modeling in offshore and earthquake engineering. The spectrum of topics include, but is not limited to, soil behavior, soil dynamics, earthquake site response analysis, soil liquefactions, as well as the modeling and assessment of shallow and deep foundations. The author provides the reader with both theory and practical applications, and thoroughly links the methodological approaches with engineering applications. The book also contains cutting-edge developments in offshore foundation engineering such as anchor piles, suction piles, pile torsion modeling, soil ageing effects and scour estimation. The target audience primarily comprises research experts and practitioners in the field of offshore engineering, but the book may also be beneficial for graduate students.

Download or read book Analysis and Design of Shallow and Deep Foundations written by Lymon C. Reese and published by John Wiley & Sons. This book was released on 2005-11-25 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: One-of-a-kind coverage on the fundamentals of foundation analysis and design Analysis and Design of Shallow and Deep Foundations is a significant new resource to the engineering principles used in the analysis and design of both shallow and deep, load-bearing foundations for a variety of building and structural types. Its unique presentation focuses on new developments in computer-aided analysis and soil-structure interaction, including foundations as deformable bodies. Written by the world's leading foundation engineers, Analysis and Design of Shallow and Deep Foundations covers everything from soil investigations and loading analysis to major types of foundations and construction methods. It also features: * Coverage on computer-assisted analytical methods, balanced with standard methods such as site visits and the role of engineering geology * Methods for computing the capacity and settlement of both shallow and deep foundations * Field-testing methods and sample case studies, including projects where foundations have failed, supported with analyses of the failure * CD-ROM containing demonstration versions of analytical geotechnical software from Ensoft, Inc. tailored for use by students in the classroom

Download or read book An Introduction to Deep Foundations and Sheet piling written by Donovan Henry Lee and published by . This book was released on 1961 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Introduction to Pile Foundations for Structures for Professional Engineers written by J. Paul Guyer, P.E., R.A. and published by Guyer Partners. This book was released on 2023-11-24 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory technical guidance for civil engineers, structural engineers, geotechnical engineers and construction managers interested construction of pile foundations. Here is what is discussed: 1. INTRODUCTION, 2. TYPES OF PILE FOUNDATIONS, 3. SELECTION OF PILE FOUNDATIONS.

Download or read book Nondestructive Testing of Deep Foundations written by Bernard Hertlein and published by John Wiley & Sons. This book was released on 2007-01-11 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nondestructive Testing involves the use of methods such as wave propagation, electromagnetism, electrical conductivity, and thermal conductivity to test structural integrity and thereby allow nondestructive assessment of structures and the possibility of structural failures before they occur. Nondestructive Testing of Deep Foundations covers different techniques designed to provide information about the integrity and quality of the material that makes up a deep foundation. Nondestructive Testing methods are used at all stages of a structure's life - from new construction quality control to residual lifetime prediction, and even during the monitoring of demolition. In addition, Nondestructive Testing is being increasingly specified in deep foundation projects, though often without a good understanding of its limitations and with the result that methods are often misused. In order to be able to specify an appropriate method, or to recognize an inappropriate specification, it is necessary for the engineer, specifier and/or contractor to understand the capabilities and limitations of each of the methods currently in use. Nondestructive Testing of Deep Foundations: Describes the most commonly used deep foundation construction techniques, including typical use of material Provides a brief history of the development of commercially available nondestructive methods Summarises each method's capabilities and limitations Acts as a one stop reference drawing together resources only previously available in conference proceedings and journal papers This manual will prove to be a welcome addition to the bookshelf of all practitioners in civil/structural and geotechnical engineering and architecture. It will also provide a valuable insight into this highly technical field for university researchers, lecturers and postgraduate students in civil/structural and geotechnical engineering.

Download or read book An Introduction to Deep Foundations for Professional Engineers written by J. Paul Guyer, P.E., R.A. and published by Guyer Partners. This book was released on 2023-01-21 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory technical guidance for civil engineers, structural engineers, geotechnical engineers and construction managers interested in foundations for buildings and structures. Here is what is discussed: 1. GENERAL, 2. FLOATING FOUNDATIONS, 3. SETTLEMENTS OF COMPENSATED FOUNDATIONS, 4. UNDERPINNING, 5. EXCAVATION PROTECTION, 6. DRILLED PIERS, 7. FOUNDATION SELECTION CONSIDERATIONS, 8. FOUNDATION DESIGN IN COLD REGIONS

Download or read book An Introduction to Deep Foundations for Professional Engineers written by J Paul Guyer and published by Independently Published. This book was released on 2023-01-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory technical guidance for civil engineers, structural engineers, geotechnical engineers and construction managers interested in foundations for buildings and structures. Here is what is discussed: 1. GENERAL, 2. FLOATING FOUNDATIONS, 3. SETTLEMENTS OF COMPENSATED FOUNDATIONS, 4. UNDERPINNING, 5. EXCAVATION PROTECTION, 6. DRILLED PIERS, 7. FOUNDATION SELECTION CONSIDERATIONS, 8. FOUNDATION DESIGN IN COLD REGIONS

Download or read book Foundations of Machine Learning second edition written by Mehryar Mohri and published by MIT Press. This book was released on 2018-12-25 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.

Download or read book Basics of Foundation Design written by Bengt Fellenius and published by Lulu.com. This book was released on 2017-03-17 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: The "Red Book" presents a background to conventional foundation analysis and design. The text is not intended to replace the much more comprehensive 'standard' textbooks, but rather to support and augment these in a few important areas, supplying methods applicable to practical cases handled daily by practising engineers and providing the basic soil mechanics background to those methods. It concentrates on the static design for stationary foundation conditions. Although the topic is far from exhaustively treated, it does intend to present most of the basic material needed for a practising engineer involved in routine geotechnical design, as well as provide the tools for an engineering student to approach and solve common geotechnical design problems.

Download or read book Advances in Designing and Testing Deep Foundations written by Michael W. O'Neill and published by . This book was released on 2005 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Designing and Testing Deep Foundations contains 25 papers on designing, constructing, and testing various types of piles and piled rafts. This Geotechnical Special Publication No. 129 honors the late Professor Michael W. O'Neill, Ph.D., P.E., a distinguished educator and researcher who made significant contributions toward the advancement of the state-of-the-art and state-of-the-practice of deep foundations. Professor O'Neill played a critical role in investigating the load transfer mechanisms of various types of piles in soils and rocks and was internationally known for his work on drilled shafts, augered piles, and field testing of various types of piles. This publication is an effective means of sharing the advances in deep foundations with practitioners, researchers, and designers.

Download or read book Introduction to Deep Learning written by Sandro Skansi and published by Springer. This book was released on 2018-02-04 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website. Topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-forward neural network; describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning; presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism. This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology.

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.