Results 1 to 10 of about 374,385 (274)

Gaussian Process Regression for numerical wind speed prediction enhancement

Renewable Energy, 2020
Haoshu Cai, Xiaodong Jia, Jianshe Feng
exaly  

Fast Gaussian Process Regression for Big Data

Big Data Research, 2018
Sourish Das, Sasanka Roy, Rajiv Sambasivan   +2 more
exaly  

Gaussian Process Functional Regression Modeling for Batch Data

Biometrics, 2007
Bo Wang, Roderick Murray-Smith
exaly  

Modelling pile capacity using Gaussian process regression

Computers and Geotechnics, 2010
Mahesh Pal, Surinder Deswal
exaly  

Monthly streamflow forecasting using Gaussian Process Regression

Journal of Hydrology, 2014
Alexander Sun, Dingbao Wang, Xianli Xu
exaly  

Stream water temperature prediction based on Gaussian process regression

Expert Systems With Applications, 2013
Ratko Grbić
exaly  

Spatial Gaussian Process Regression With Mobile Sensor Networks

IEEE Transactions on Neural Networks and Learning Systems, 2012
Dongbing Gu, Huosheng Hu
exaly  

Prognostic health condition for lithium battery using the partial incremental capacity and Gaussian process regression

Journal of Power Sources, 2019
Zhenpo Wang
exaly  

Reliable multi-objective optimization of high-speed WEDM process based on Gaussian process regression

International Journal of Machine Tools and Manufacture, 2008
exaly  

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   +5 more sources