Handbook of Machine Foundations
Author | : P. Srinivasulu |
Publisher | : |
Total Pages | : 264 |
Release | : 1977 |
Genre | : MACHINERY |
ISBN | : |
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Author | : P. Srinivasulu |
Publisher | : |
Total Pages | : 264 |
Release | : 1977 |
Genre | : MACHINERY |
ISBN | : |
Author | : K.G. Bhatia |
Publisher | : CRC Press |
Total Pages | : 0 |
Release | : 2009-10-12 |
Genre | : Technology & Engineering |
ISBN | : 9788190603201 |
The performance, safety and stability of machines depends largely on their design, manufacturing and interaction with environment. Machine foundations should be designed in such a way that the dynamic forces transmitted to the soil through the foundation, eliminating all potentially harmful forces. This handbook is designed primarily for the practising engineers engaged in design of machine foundations. It covers basic fundamentals for understanding and evaluating dynamic response of machine foundation systems with emphasis is on detailed dynamic analysis for response evaulation. Use of commercially available Finite Element packages, for analysis and design of the foundation, is recommended. Theory is supported by results from practice in the form of examples.
Author | : Sun, Zhaohao |
Publisher | : IGI Global |
Total Pages | : 425 |
Release | : 2022-03-11 |
Genre | : Computers |
ISBN | : 179989018X |
Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.
Author | : P. Srinivasulu |
Publisher | : |
Total Pages | : 0 |
Release | : 1976 |
Genre | : |
ISBN | : |
Author | : Suresh C. Arya |
Publisher | : Gulf Publishing |
Total Pages | : 216 |
Release | : 1979 |
Genre | : Technology & Engineering |
ISBN | : |
This text brings together traditional and new concepts and procedures for analyzing and designing dynamically loaded structures.
Author | : Avrim Blum |
Publisher | : Cambridge University Press |
Total Pages | : 433 |
Release | : 2020-01-23 |
Genre | : Computers |
ISBN | : 1108617360 |
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author | : Jeremy Watt |
Publisher | : Cambridge University Press |
Total Pages | : 597 |
Release | : 2020-01-09 |
Genre | : Computers |
ISBN | : 1108480721 |
An intuitive approach to machine learning covering key concepts, real-world applications, and practical Python coding exercises.
Author | : Marc Peter Deisenroth |
Publisher | : Cambridge University Press |
Total Pages | : 392 |
Release | : 2020-04-23 |
Genre | : Computers |
ISBN | : 1108569323 |
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Author | : |
Publisher | : Univalent Foundations |
Total Pages | : 484 |
Release | : |
Genre | : |
ISBN | : |
Author | : Ulrich Smoltczyk |
Publisher | : John Wiley & Sons |
Total Pages | : 716 |
Release | : 2003-03-14 |
Genre | : Technology & Engineering |
ISBN | : 9783433014509 |
Volume 2 of the Handbook covers the geotechnical procedures used in manufacturing anchors and piles as well as for improving or underpinning foundations, securing existing constructions, controlling ground water, excavating rocks and earth works. It also treats such specialist areas as the use of geotextiles and seeding.