Results 1 to 10 of about 11,061,498 (228)
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Nonnegativity-enforced Gaussian process regression
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Design Support of function of brassiere cup using gaussian process regression
Nihon Kikai Gakkai ronbunshu, 2021 A method to design the function of the brassiere cup shape as developable surfaces and its developed shape using Gaussian Process Regression is proposed.
Kotaro YOSHIDA +3 more
doaj +1 more source
Revisiting cosmography via Gaussian process
European Physical Journal C: Particles and Fields, 2023 In this paper, we revisit the kinematical state of our Universe via the cosmographic approach by using Gaussian process, where the minimum assumption is the cosmological principle, i.e. the Friedmann–Lemaître–Robertson–Walker metric.
Jinyi Liu +3 more
doaj +1 more source
Scenario Optimisation and Sensitivity Analysis for Safe Automated Driving Using Gaussian Processes
Applied Sciences, 2021 Assuring the safety of automated vehicles is essential for their timely introduction and acceptance by policymakers and the public. To assess their safe design and robust decision making in response to all possible scenarios, new methods that use a ...
Felix Batsch +3 more
doaj +1 more source