Results 11 to 20 of about 14,298 (230)

Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML). [PDF]

Smart Sustain Manuf Syst, 2017
ABSTRACT This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data.
Park J, Lechevalier D, Ak R, Ferguson M, Law KH, Lee YT, Rachuri S.   +6 more
europepmc   +5 more sources

Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing microencapsulated PCMs. [PDF]

Sci Rep
AbstractSuspensions containing microencapsulated phase change materials (MPCMs) play a crucial role in thermal energy storage (TES) systems and have applications in building materials, textiles, and cooling systems. This study focuses on accurately predicting the dynamic viscosity, a critical thermophysical property, of suspensions containing MPCMs and
Hai T, Basem A, Alizadeh A, Sharma K, Jasim DJ, Rajab H, Ahmed M, Kassim M, Singh NSS, Maleki H.   +9 more
europepmc   +4 more sources

EVARS-GPR: EVent-Triggered Augmented Refitting of Gaussian Process Regression for Seasonal Data [PDF]

, 2021
Time series forecasting is a growing domain with diverse applications. However, changes of the system behavior over time due to internal or external influences are challenging. Therefore, predictions of a previously learned fore-casting model might not be useful anymore.
Florian Haselbeck, Dominik G. Grimm
openaire   +2 more sources

Application of Gaussian Process Regression (GPR) in Gas Hydrate Mitigation

Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 2021
The production of oil and natural gas contributes to a significant amount of revenue generation in Malaysia thereby strengthening the country’s economy. The flow assurance industry is faced with impediments during smooth operation of the transmission pipeline in which gas hydrate formation is the most important.
null Sachin Dev Suresh, null Ali Qasim, null Bhajan Lal, null Syed Muhammad Imran, null Khor Siak Foo   +4 more
openaire   +2 more sources

Twenty-Four-Hour Ahead Probabilistic Global Horizontal Irradiance Forecasting Using Gaussian Process Regression

Algorithms, 2021
Probabilistic solar power forecasting has been critical in Southern Africa because of major shortages of power due to climatic changes and other factors over the past decade. This paper discusses Gaussian process regression (GPR) coupled with core vector
Edina Chandiwana, Caston Sigauke, Alphonce Bere   +2 more
doaj   +1 more source

A Precessing Numerical Relativity Waveform Surrogate Model for Binary Black Holes: A Gaussian Process Regression Approach [PDF]

, 2020
Gravitational wave astrophysics relies heavily on the use of matched filtering both to detect signals in noisy data from detectors, and to perform parameter estimation on those signals.
Clark, James A, Gair, Jonathan, Heng, Ik Siong, Khamesra, Bhavesh, Williams, Daniel   +4 more
core   +2 more sources

Selecting Hyper-Parameters of Gaussian Process Regression Based on Non-Inertial Particle Swarm Optimization in Internet of Things

IEEE Access, 2019
Gaussian process regression (GPR) is frequently used for uncertain measurement and prediction of nonstationary time series in the Internet of Things data, nevertheless, the generalization and regression efficacy of GPR are directly impacted by its ...
Lanlan Kang, Ruey-Shun Chen, Naixue Xiong, Yeh-Cheng Chen, Yu-Xi Hu, Chien-Ming Chen   +5 more
doaj   +1 more source

Performance evaluation of friction stir welding using machine learning approaches

MethodsX, 2018
The aim of the present study is to evaluate the potential of sophisticated machine learning methodologies, i.e. Gaussian process (GPR) regression, support vector machining (SVM), and multi-linear regression (MLR) for ultimate tensile strength (UTS) of ...
Shubham Verma, Meenu Gupta, Joy Prakash Misra   +2 more
doaj   +1 more source

Regression-based Multi-View Facial Expression Recognition [PDF]

, 2010
We present a regression-based scheme for multi-view facial expression recognition based on 2-D geometric features. We address the problem by mapping facial points (e.g.
Pantic, Maja, Patras, Ioannis, Rudovic, Ognjen   +2 more
core   +3 more sources

Nonlinear Channel Equalization based on Gaussian Processes for Regression in Fiber Link

Guangtongxin yanjiu, 2022
In order to mitigate the effect of nonlinear noise nonlinear Channel Equalizer (CE) based on Gaussian Processes for Regression (GPR) is proposed and experimentally demonstrated in an intensity modulation and direct detection fiber link.
WU Biao, LI Jia-hao, ZHANG Zhao-cai
doaj   +3 more sources