Effects of combined dimension reduction and tabulation on the ...

Effects of combined dimension reduction and tabulation on the simulations of a turbulent premixed flame using a large-eddy simulation ...

Effects of combined dimension reduction and tabulation on the simulations of a turbulent premixed flame using a large-eddy simulation/probability density ...

Effects of combined dimension reduction and tabulation on the ...

A turbulent lean-premixed propane-air flame stabilised by a triangular cylinder as a flame-holder is simulated to assess the accuracy and computational ...

Assessment of On-the-Fly Chemistry Reduction and Tabulation ...

(12) combined chemistry dimension reduction and tabulation with a ... In this study, we quantify the impact of multi-dimensional effects ...

An efficient time scale model with tabulation of chemical equilibrium

Simulations of a turbulent non-premixed flame using combined dimension reduction and tabulation for combustion chemistry ... The impact of the reduced ...

Simulations of a turbulent non-premixed flame using combined ...

DAC and dimension reduction methods have been routinely employed in combination with tabulation methods to accelerate the necessary chemistry integration by ...

Reduced Description of Reactive Flows with Tabulation of Chemistry

develop a general, combined dimension reduction/tabulation methodology for the ... the reduced description is to model the effect of chemical reactions on the ...

Large-scale parallel simulations of turbulent combustion using ...

to represent the effects of subgrid-scale turbu- ... ISAT/RCCE: combined dimension reduction and tabulation with a reduced representation.

Assessment of On-the-Fly Chemistry Reduction and Tabulation ...

combined chemistry dimension reduction and tabulation with a methodology ... dimensional effects on the auto-ignition of the iso-octane. Proc. Combust ...

6.1: Cross-Tabulation - Statistics LibreTexts

For that type of case, we may use a reduction in error or a proportional reduction in error (PRE) model. ... size and the dimensions of the table.

Implementation of combustion chemistry by in situ adaptive ...

This method combines dimension reduction and tabulation and can be implemented in a single computer program, which is independent of the detailed mechanism ...

Simulations of a turbulent non-premixed flame using combined ...

Semantic Scholar extracted view of "Simulations of a turbulent non-premixed flame using combined dimension reduction and tabulation for ...

Cross-Tabulation Analysis: A Full Guide (+ Examples) | Appinio Blog

Data Reduction Techniques: Apply data reduction ... Cramer's V: Compute Cramer's V statistic as a measure of effect size for the association ...

On the Effects of Dimensionality Reduction on High ... - CiteSeerX

The dimensionality curse has profound effects on the ef- fectiveness of high-dimensional similarity indexing from the performance perspective. One of the well ...

Dimensionality Reduction Meaning, Techniques, and Examples

Dimensionality reduction is defined as a method of reducing variables in a training dataset used to develop machine learning models.

Estimation for Cells Suppressed in Tabulation with Application to ...

It is limited to 3-dimensions and requires combining variables from a higher dimensional table in order to reduce it to 3-dimensions. Also it requires ...

Introduction to Data Science - 22 Dimension reduction

The general idea is to reduce the dimension of the dataset while preserving important characteristics, such as the distance between features or observations.

arXiv:2210.13230v3 [cs.LG] 22 Mar 2023

Previous work examining the effects of different dimension reduction techniques within machine learning algorithms is sparse. Reddy and ...

Locally-Adaptive Tabulation of Low-Dimensional Manifolds using ...

The advantages of dimension reduction combined with a priori tabulation are well accepted and used in a number ... heat transfer effects, partial premixing ...

Exploring combinations of dimensionality reduction, transfer ...

We examined the impact of using latent representations with fewer predictors generated through PCA or c-ICA on the performance of predictive ...