Research on Dimension Reduction Method for Combustion ...

Scientific Machine Learning - Karen E. Willcox

Predicting combustion instabilities requires new capabilities in scientific machine learning, nonlinear model reduction, data-driven reduced models, and multi- ...

Threefold way to the dimension reduction of dynamics on networks

... dimensional reduction method, as used in Ref. [27]. We then need to ... Reduced dynamics. We study a specific case of the SBM, namely ...

Dimensionality reduction and feature extraction from high-fidelity ...

The webinars review some of the open opportunities for the application of data-driven, reduced-order modelling to combustion systems. In particular, the first ...

Variable dimensionality reduction modeling method for boiler ...

The invention belongs to the technical field of a heat engineering technology and an artificial intelligence crossing technology, and relates to a variable ...

Reduced Dimension Analysis on Combustion Oscillation in a Model ...

This study introduces a new method for the dimension ... dimension reduction methods has potential to distinguish between the two different combustion modes.

Homogenization and dimension reduction of filtration combustion in ...

We recover the reduced macroscopic equations from [25] with precise formulas for the effective transport and reaction coefficients. We complement the analytical ...

Dimension Reduction of Chemical Process Simulation Data

Section 3 covers application of the method to a methane combustion pro- cess. Section 4 has details of the subgroup discovery method used in REDSUB. Section 5 ...

Toward real-time volumetric tomography for combustion diagnostics ...

The development of these methods provides an unprecedented opportunity to understand the complicated turbulent combustion phenomena such as the acoustic ...

Tangentially Fired Boiler Combustion Optimization based on ...

Simulation results reveal that the dimension-reduction method can significantly accelerate the computation by condensing the model structure, without impacting ...

A New Data Dimension Reduction Method Based On Convolution In ...

In this study, unsupervised learning method was used to model and identify LongGu, calcining LongGu and LongGu counterfeits by infrared spectroscopy.

Co-kurtosis tensor | Konduri Aditya - CDS, IISc

A co-kurtosis based dimensionality reduction method for combustion datasets ... Principal Component Analysis (PCA) is a dimensionality reduction technique widely ...

Intro - Neuromatch Academy: Computational Neuroscience

Finally, in Tutorial 4, you will briefly be introduced to a second dimensionality reduction method, a non-linear method called t-SNE. You'll hear from Byron ...

Machine Learning Yields More Efficient Hydrogen Combustion ...

With this new hybrid model, the researchers realized two orders of magnitude reduction ... Our new ML/physics-inspired method uses diffusion ...

Data-driven models and digital twins for sustainable combustion ...

While non-linear methods enhance dimensionality reduction, they are more challenging regarding physical interpretation and can be ...

Comparison of dimension reduction techniques in the analysis of ...

In atmospheric studies, the most exploited method, especially in the analysis of long time series of aerosol mass spectrometer (AMS) data ...

What is Dimensionality Reduction? | IBM

Dimensionality reduction is a method for representing a given dataset using a lower number of features (ie dimensions) while still capturing the original data' ...

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

Dive into the research topics of 'Effects of combined dimension reduction and tabulation on the simulations of a turbulent premixed flame using a large-eddy ...

Comparing different nonlinear dimensionality reduction techniques ...

In this study, we provide a detailed qualitative (mode patterns) and quantitative (reconstruction error) comparison of these methods.

Applied Dimensionality Reduction — 3 Techniques using Python

The second part of this article walks you through a case study, where we get our hands dirty and use python to 1) reduce the dimensions of an image dataset and ...

Homogenization and dimension reduction of filtration combustion in ...

We study the homogenization of a reaction-diffusion-convection system posed in an ε-periodic δ-thin layer made of a two-component (solid-air).