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Erschienen in:
Automatic Object Detection from Digital Images by Deep Learning with Transfer Learning Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Data Driven Analytics (Machine Learning) for System Characterization, Diagnostics and Control Optimization

verfasst von : Jinkyoo Park, Max Ferguson, Kincho H. Law

Erschienen in: Advanced Computing Strategies for Engineering

Verlag: Springer International Publishing

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Abstract

This presentation discusses the potential use of machine learning techniques to build data-driven models to characterize an engineering system for performance assessment, diagnostic analysis and control optimization. Focusing on the Gaussian Process modeling approach, engineering applications on constructing predictive models for energy consumption analysis and tool condition monitoring of a milling machine tool are presented. Furthermore, a cooperative control optimization approach for maximizing wind farm power production by combining Gaussian Process modeling with Bayesian Optimization is discussed.

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Vorheriges Kapitel Automatic Object Detection from Digital Images by Deep Learning with Transfer Learning
Nächstes Kapitel 3D Imaging in Construction and Infrastructure Management: Technological Assessment and Future Research Directions
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Metadaten
Titel
Data Driven Analytics (Machine Learning) for System Characterization, Diagnostics and Control Optimization
verfasst von
Jinkyoo Park
Max Ferguson
Kincho H. Law
Copyright-Jahr
2018
Buch
Advanced Computing Strategies for Engineering

Print ISBN: 978-3-319-91634-7

Electronic ISBN: 978-3-319-91635-4

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-91635-4_2

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