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Titlebook: Modelling and Control of Dynamic Systems Using Gaussian Process Models; Ju? Kocijan Book 2016 Springer International Publishing Switzerlan

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發(fā)表于 2025-3-21 20:02:58 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Modelling and Control of Dynamic Systems Using Gaussian Process Models
編輯Ju? Kocijan
視頻videohttp://file.papertrans.cn/637/636567/636567.mp4
概述Explains how theoretical work in Gaussian process models can be applied in the control of real industrial systems.Provides the engineer with practical guidance is not unduly encumbered by complicated
叢書(shū)名稱Advances in Industrial Control
圖書(shū)封面Titlebook: Modelling and Control of Dynamic Systems Using Gaussian Process Models;  Ju? Kocijan Book 2016 Springer International Publishing Switzerlan
描述.This monograph opens up new horizons for engineers and researchers inacademia and in industry dealing with or interested in new developments in thefield of system identification and control. It emphasizes guidelines forworking solutions and practical advice for their implementation rather than thetheoretical background of Gaussian process (GP) models. The book demonstratesthe potential of this recent development in probabilistic machine-learningmethods and gives the reader an intuitive understanding of the topic. Thecurrent state of the art is treated along with possible future directions forresearch..Systems control design relies on mathematical models and these may bedeveloped from measurement data. This process of system identification, whenbased on GP models, can play an integral part of control design in data-basedcontrol and its description as such is an essential aspect of the text. Thebackground of GP regression is introduced first with system identification andincorporation of prior knowledge then leading into full-blown control. The bookis illustrated by extensive use of examples, line drawings, and graphicalpresentation of computer-simulation results and plant measureme
出版日期Book 2016
關(guān)鍵詞Atmospheric Ozone; Fault Detection; Fault Diagnosis; Gas–Liquid Separator; Gaussian Process Model; Hydrau
版次1
doihttps://doi.org/10.1007/978-3-319-21021-6
isbn_softcover978-3-319-79327-6
isbn_ebook978-3-319-21021-6Series ISSN 1430-9491 Series E-ISSN 2193-1577
issn_series 1430-9491
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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1430-9491 poration of prior knowledge then leading into full-blown control. The bookis illustrated by extensive use of examples, line drawings, and graphicalpresentation of computer-simulation results and plant measureme978-3-319-79327-6978-3-319-21021-6Series ISSN 1430-9491 Series E-ISSN 2193-1577
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Advances in Industrial Controlhttp://image.papertrans.cn/m/image/636567.jpg
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https://doi.org/10.1007/978-3-319-21021-6Atmospheric Ozone; Fault Detection; Fault Diagnosis; Gas–Liquid Separator; Gaussian Process Model; Hydrau
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Modelling and Control of Dynamic Systems Using Gaussian Process Models978-3-319-21021-6Series ISSN 1430-9491 Series E-ISSN 2193-1577
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發(fā)表于 2025-3-23 03:09:56 | 只看該作者
Book 2016eld of system identification and control. It emphasizes guidelines forworking solutions and practical advice for their implementation rather than thetheoretical background of Gaussian process (GP) models. The book demonstratesthe potential of this recent development in probabilistic machine-learning
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