Structural Health Monitoring: A Machine Learning Perspective
| Author | : | |
| Rating | : | 4.59 (871 Votes) |
| Asin | : | 1119994330 |
| Format Type | : | paperback |
| Number of Pages | : | 654 Pages |
| Publish Date | : | 2017-04-02 |
| Language | : | English |
DESCRIPTION:
The authors, renowned experts in the field, consider structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm, first explaining the paradigm in general terms then explaining the process in detail with further insight provided via numerical and experimental studies of laboratory test specimens and in-situ structures. Written by global leaders and pioneers in the field, this book is a must-have read for researchers, practicing engineers and university faculty working in SHM.Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book
From the Back CoverElectrical Installation Designs is the only book on electrical installation practice that uses typical projects to illustrate how to produce designs that comply with current standards. This Fourth Edition has been revised and updated to take account of the 2011 Amendment to the Seventeenth Edition of the Wiring Regulations BS 7671: 2008. It offers a practical guide on how to design and complete a range of electrical installation projects in a way to ensure compliance with these new Wiring Regulations. Examining projects including domestic, commercial, industrial, agricultural, and leisure complexes, the authors explain the requirements of earthing and bonding, isolation and switching, o
He serves on the editorial boards of 2 international journals: Journal of Sound and Vibration and Mechanical Systems and Signal Processing. In 2000 he founded the Los Alamos Dynamics Summer School. He was awarded "2004 Person of the Year" (jointly with W.J. He is currently working with engineering faculty at University of California, San Diego to develop the Los Alamos/UCSD Engineering Institute and Education Initiative with a rese
"Excellent Resource for SHM" according to Matthew. I have read this book, cover-to-cover. It is excellent. It presents a structured framework for solving pattern recognition problems of just about any type. While it goes into a significant depth of detail, the scope of the book is too broad to provide full details for all procedures. Instead, the authors provide an overview of the framework, peppered with many examples and enough details to get a beginner going. The authors provide a wealth of references for in-depth details abou. Four Stars It is good though I expected that pictures in color.