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OverviewFull Product DetailsAuthor: Ramin Madarshahian , François HemezPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 1st ed. 2023 Weight: 0.745kg ISBN: 9783031349454ISBN 10: 3031349458 Pages: 188 Publication Date: 08 December 2023 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsChapter 1. A Meta-Learning Approach to Population-Based Modelling of Structure.-, Chapter 2 State Space Reconstruction from Embeddings of Partial Observables in Structural Dynamic Systems for Structure-Preserving Data-Driven Methods.-, Chapter 3 Chapter 2. State Space Reconstruction from Embeddings of Partial Observables in Structural Dynamic Systems for Structure-Preserving Data-Driven Methods.-, Chapter 4 Composite Neural Network Framework for Modeling Impulsive Nonlinear Dynamic Responses.-, Chapter 5 Towards physics-based metrics for transfer learning in dynamics.-, Chapter 6 Principal Component Analysis of Monitoring Data of a High-Rise Building: The Case Study of Palazzo Lombardia.-, Chapter 7 Optimal Contact-Impact Force Model Selection for Damage Detection in Ball Bearings.-, Chapter 8 Simulation Error Influence on Damage Identification Classifiers Trained by Numerical Data.-, Chapter 9 Structural Health Monitoring in the Context ofNon-Equilibrium Phase Transitions.-, Chapter 10 Synthetic Thermal Image Data Generation using Attention-Based Generative Adversarial Network for Concrete Internal Damage Segmentation.-, Chapter 11 Optimal Fiber Optic Sensor Placement Framework for Structural Health Monitoring of an Aircraft’s Wing Spar.-, Chapter 12 Construction Noise Cancellation with Feedback Active Control using Machine Learning.-, Chapter 13 Physics-Informed Data-Driven Reduced-Order Model for Turbomachinery Blisk.-, Chapter 14 High-rate Structural Health Monitoring: Part-II Embedded System Design.-, Chapter 15 Damage Quantification under High-Rate Dynamic Loading and Data Augmentation using Generative Adversarial Network.-, Chapter16 Output-only versus Direct Input-output Structural Condition Monitoring Methods.-, Chapter 17 High-rate Structural Health Monitoring: Part-III Algorithm.-, Chapter 18 A population form via hierarchical Bayesian modelling of the FRF.-, Chapter 19 Lupos: Open-source Scientific Computing in Structural Dynamics.-, Chapter 20 Expert Knowledge-Driven Condition Assessment of Railway Welds from Axle Box Accelerations using Random Forests and Bayesian Logistic Regression.-, Chapter 21 On quantifying data normalisation via cointegration with topological methods.-, Chapter 22 Automatic Selection of Optimal Structures for Population-based Structural Health Monitoring.-, Chapter 23 Online back-propagation of recurrent neural network for forecasting nonstationary structural responses.ReviewsAuthor InformationRamin Madarshahian–Company: Kount, an Equifax company, Boise, ID, USA ;Francois Hemez–Lawrence Livermore National Laboratory, Livermore, CA, USA Tab Content 6Author Website:Countries AvailableAll regions |
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