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Nonnegativity-enforced Gaussian process regression [PDF]
Theoretical and Applied Mechanics Letters, 2020 : Gaussian process (GP) regression is a flexible non-parametric approach to approximate complex models. In many cases, these models correspond to processes with bounded physical properties.
Andrew Pensoneault, Xiu Yang, Xueyu Zhu
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Modelling of Li-Ion battery state-of-health with Gaussian processes [PDF]
Archives of Electrical Engineering, 2023 The problem of lithium-ion cells, which degrade in time on their own and while used, causes a significant decrease in total capacity and an increase in inner resistance. So, it is important to have a way to predict and simulate the remaining usability of
Adrian Dudek, Jerzy Baranowski
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A set-based approach to dynamic system design using physics informed neural network
Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2022 In the early stage of dynamic system development which has a multi-disciplinary and hierarchical structure, system requirements need to be cascaded down to target values of each component so that engineers can collaborate efficiently and concurrently ...
Kohei SHINTANI +2 more
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Oscillating Gaussian processes [PDF]
Statistical Inference for Stochastic Processes, 2020 AbstractIn this article we introduce and study oscillating Gaussian processes defined by$$X_t = \alpha _+ Y_t \mathbf{1}_{Y_t >0} + \alpha _- Y_t\mathbf{1}_{Y_t<0}$$Xt=α+Yt1Yt>0+α-Yt1Yt<0, where$$\alpha _+,\alpha _->0$$α+,α->0are free parameters andYis either stationary or self-similar Gaussian process.
Ilmonen, Pauliina +2 more
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Generating random terrains in 3D games by an approximated version of Gaussian process
Tạp chí Khoa học, 2023 Creating a 3D terrain or a wave surface takes a lot of time for a graphic artist in the 3D game creation process. This problem poses the following computer requirements: the generated terrain surface must be both random at all points, but also smooth and
DANG Viet Hung, VO Van Nhan
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Prediction on α-decay Energy of Heavy and Superheavy Nuclei Using Machine Learning
Yuanzineng kexue jishu, 2023 α-decay is one of the most dominant decay modes of unstable nuclei. It is helpful for the investigation of exotic nuclear structures. Moreover, α-decay is a powerful tool for identifying the newly synthesized nuclides for heavy and superheavy nuclei in ...
YUAN Ziyi;REN Zhongzhou;BAI Dong;WANG Zhen
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IET Intelligent Transport Systems, 2023 Vehicle‐to‐Everything (V2X) communication has been proposed as a potential solution to improve the robustness and safety of autonomous vehicles by improving coordination and removing the barrier of non‐line‐of‐sight sensing.
Rodolfo Valiente +5 more
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Journal of Hydroinformatics, 2023 This paper explores the ability of multivariate adaptive regression splines, decision trees, Gaussian processes, and multiple non-linear regression equation approaches to predict the aeration efficiency at various weirs and discusses their results.
Akash Jaiswal, Arun Goel, Parveen Sihag
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Journal of Marine Science and Engineering, 2021 Maritime transport plays a vital role in economic development. To establish a vessel scheduling model, accurate ship maneuvering models should be used to optimize the strategy and maximize the economic benefits.
Yifan Xue +3 more
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Compositionally-warped Gaussian processes [PDF]
Neural Networks, 2019 Accepted at Elsevier Neural Networks, DOI added and author order ...
Gonzalo Rios, Felipe Tobar
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