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Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes [PDF]
Sensors, 2018 This study applied the kriging model and particle swarm optimization (PSO) algorithm for the dynamic model updating of bridge structures using the higher vibration modes under large-amplitude initial conditions.
Shiqiang Qin +3 more
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The quasi-fiducial model selection for Kriging model
Statistical Theory and Related FieldsKriging models are widely employed due to their simplicity and flexibility in a variety of fields. To gain more distributional information about the unknown parameters, we focus on constructing the fiducial distribution of Kriging model parameters.
Chen Fan, Shuqin Zhang, Xinmin Li
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Optimization of Ski Attitude for the In-Flight Aerodynamic Performance of Ski Jumping
Biology, 2022 The control and adjustment of in-flight attitudes are critical to enlarging the flight distance of ski jumping. As one of the most important gears, the skis provide sufficient lift and drag forces for the athletes, and thus their in-flight attitudes ...
Lianzhong Cao +5 more
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Applied Sciences, 2022 Reactive powder concrete-filled steel tube (RPC-FST) is a critical supporting component of large-span, high-rise, and heavy-load structures. The collapse of RPC-FST may occur under explosive load.
Zhizhong Jiang +4 more
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Hangkong gongcheng jinzhan, 2022 The civil aircraft spare parts support network is a necessary medium for the main manufacturer to provide customers with aviation materials. The rationality of its construction is conducive to improving the service quality of the main manufacturer and ...
WEI Yanfeng, QIAO Linjun
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Zhongguo Jianchuan Yanjiu, 2021 ObjectivesThe cabin-skeleton coupling structure of a blended-wing-body underwater glider is optimized using a data-driven discrete optimization concept.MethodsFirst, a Kriging-assisted discrete global optimization algorithm (KDGO) is proposed for ...
Huachao DONG, Peng WANG, Yijin ZHANG
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Lifted Brownian Kriging Models [PDF]
Technometrics, 2017 Gaussian processes have become a standard framework for modeling deterministic computer simulations and producing predictions of the response surface. This article investigates a new covariance function that is shown to offer superior prediction compared to the more common covariances for computer simulations of real physical systems.
Matthew Plumlee, Daniel W. Apley
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Aerospace, 2023 To achieve the low-cycle fatigue (LCF) lifetime prediction and reliability estimation of turbine blisks, a Marine Predators Algorithm (MPA)-based Kriging (MPA-Kriging) method is developed by introducing the MPA into the Kriging model.
Gaiya Feng, Jiongran Wen, Chengwei Fei
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Mathematics, 2021 The Kriging surrogate model in complex simulation problems uses as few expensive objectives as possible to establish a global or local approximate interpolation.
Yaohui Li +5 more
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On the use of gradients in Kriging surrogate models [PDF]
Proceedings of the Winter Simulation Conference 2014, 2014 The use of Kriging surrogate models has become popular in approximating computation-intensive deterministic computer models. In this work, the effect of enhancing Kriging surrogate models with a (partial) set of gradients is investigated. While, intuitively, gradient information is useful to enhance prediction accuracy, another motivation behind this ...
Selvakumar Ulaganathan +4 more
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