Surrogate Modelling for the Prediction of Spatial Fields Based on Simultaneous Dimensionality Reduction of High-Dimensional Input/Output Spaces

Royal Society Open Science - United Kingdom
doi 10.1098/rsos.171933
Full Text
Abstract

Available in full text

Date
Authors
Publisher

The Royal Society

Related search

Towards Simultaneous Reduction of Both Input and Output Spaces for Interactive Simulation-Based Structural Design

Computer Methods in Applied Mechanics and Engineering
Mechanics of MaterialsMechanical EngineeringComputer Science ApplicationsComputational MechanicsAstronomyPhysics
2013English

FastMap in Dimensionality Reduction: Ensemble Clustering of High Dimensional Data

International Journal of Data Science
2017English

Novel Input-Output Prediction Approach for Biomass Pyrolysis

Journal of Cleaner Production
IndustrialEnvironmental ScienceRenewable EnergyManufacturing EngineeringStrategySustainabilityManagementthe Environment
2016English

On the Dimensionality Reduction for Sparse Representation Based Face Recognition

2010English

Dimensionality Reduction for Supervised Learning With Reproducing Kernel Hilbert Spaces

2003English

Uncertainty Quantification for Flow and Transport in Highly Heterogeneous Porous Media Based on Simultaneous Stochastic Model Dimensionality Reduction

Transport in Porous Media
CatalysisChemical Engineering
2018English

Prediction-Based Control of LTI Systems With Input and Output Time-Varying Delays

Systems and Control Letters
ControlSystems EngineeringMechanical EngineeringElectronic EngineeringElectricalComputer Science
2018English

Spatial Regularization of Functional Connectivity Using High-Dimensional Markov Random Fields

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2010English

Adaptive Sampling for Nonlinear Dimensionality Reduction Based on Manifold Learning

Modeling, Simulation and Applications
Computational MathematicsApplied MathematicsSimulationModeling
2017English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy