Results 21 to 30 of about 1,248,103 (272)
An automation system for vehicle driveability evaluation using machine learning
Nihon Kikai Gakkai ronbunshu, 2022 The drivability is one of the important aspects of vehicle dynamic performances. To ensure quality of the drivability performance, comprehensive screening evaluation is necessary by controlling both complicated driver operation and vehicle behavior ...
Hisashi TAJIMA +4 more
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Gaussian process model based predictive control [PDF]
, 2003 Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of non-linear dynamic systems. The Gaussian processes can highlight areas of the input space where prediction quality is poor, due to the lack ...
, +4 more
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Physical Review D, 2012 Gaussian processes provide a method for extracting cosmological information from observations without assuming a cosmological model. We carry out cosmography -- mapping the time evolution of the cosmic expansion -- in a model-independent manner using kinematic variables and a geometric probe of cosmology.
Shafieloo, Arman +2 more
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Global Optimization Employing Gaussian Process-Based Bayesian Surrogates
Entropy, 2018 The simulation of complex physics models may lead to enormous computer running times. Since the simulations are expensive it is necessary to exploit the computational budget in the best possible manner.
Roland Preuss, Udo von Toussaint
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Applied Sciences, 2019 Precise prediction of short-term electric load demand is the key for developing power market strategies. Due to the dynamic environment of short-term load forecasting, probabilistic forecasting has become the center of attention for its ability of ...
Zhengmin Kong +3 more
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Continuity of Gaussian Processes [PDF]
The Annals of Probability, 1986 The author first gives a generalization of \textit{M. B. Marcus} and \textit{L. A. Shepp}'s [Proc. Sixth Berkeley Sympos. math. Statist. Probab., Univ. Calif. 1970, 2, 423-441 (1972; Zbl 0379.60040)] theorem on the equivalence between sample continuity of a Gaussian process defined on a compact subset of a metric space, and a.s.
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Power Load Forecasting Method Based on MT-BSGP
Journal of Harbin University of Science and Technology, 2021 In order to forecast short-term household power load，a power load forecasting method based on multi-task Bayesian spatiotemporal Gaussian process ( MT-BSGP) is proposed.
LI Zhi-yong +5 more
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Sequentially Estimating the Approximate Conditional Mean Using Extreme Learning Machines
Entropy, 2020 This study examined the extreme learning machine (ELM) applied to the Wald test statistic for the model specification of the conditional mean, which we call the WELM testing procedure.
Lijuan Huo, Jin Seo Cho
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Demand response of residential air conditioning load based on user behavior
Zhejiang dianli, 2023 Residential side demand response is an important supplementary means to maintain the supply-demand balance of source-load in the power system. However， the uncertainty of user behavior makes it difficult to accurately control demand response.
LIU Yiping +5 more
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The empirical process on Gaussian spherical harmonics [PDF]
, 2004 We establish weak convergence of the empirical process on the spherical harmonics of a Gaussian random field in the presence of an unknown angular power spectrum. This result suggests various Gaussianity tests with an asymptotic justification.
Domenico Marinucci +3 more
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