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Publication . Preprint . Article . 2021

Identification of model uncertainty via optimal design of experiments applied to a mechanical press

Tristan Gally; Peter Groche; Florian Hoppe; Anja Kuttich; Alexander Matei; Marc E. Pfetsch; Martin Rakowitsch; +1 Authors
Open Access
Published: 01 Jan 2021 Journal: Optimization and Engineering, volume 23, pages 579-606 (issn: 1389-4420, eissn: 1573-2924, Copyright policy )
Publisher: Springer Science and Business Media LLC
Country: Germany
Abstract
Published by Springer Science + Business Media B.V, Dordrecht [u.a.]
Optimization and engineering (2021). doi:10.1007/s11081-021-09600-8
Subjects by Vocabulary

Microsoft Academic Graph classification: Computation Condition monitoring Computer science Control theory Variance (accounting) Component (UML) Mathematical model Statistical hypothesis testing Servo drive

Dewey Decimal Classification: ddc:690

Subjects

Electrical and Electronic Engineering, Control and Optimization, Mechanical Engineering, Aerospace Engineering, Civil and Structural Engineering, Software, Machine Learning (stat.ML), Machine Learning (cs.LG), Optimization and Control (math.OC), Applications (stat.AP), FOS: Computer and information sciences, FOS: Mathematics, 690, Statistics - Machine Learning, Computer Science - Machine Learning, Mathematics - Optimization and Control, Statistics - Applications

27 references, page 1 of 3

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[9] H. Dresig and A. Fidlin. Schwingungen mechanischer Antriebssysteme: Modellbildung, Berechnung, Analyse, Synthese. Springer, 3. auflage edition, 2014.

[10] V. V. Fedorov and S. L. Leonov. Optimal design for nonlinear response models. CRC Press, 2013.

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