Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches

Coussement, Axel; Isaac, Benjamin J.; Gicquel, Olivier; Parente, Alessandro

doi:10.1016/j.combustflame.2016.03.021

Title: Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches

Full Record
Other Related Research

Authors:: Coussement, Axel; Isaac, Benjamin J.; Gicquel, Olivier; Parente, Alessandro

Publication Date:: 2016-06-01

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1324341

Grant/Contract Number:: NA0002375

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Combustion and Flame

Additional Journal Information:: Journal Name: Combustion and Flame Journal Volume: 168 Journal Issue: C; Journal ID: ISSN 0010-2180

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Citation Formats


                    Coussement, Axel, Isaac, Benjamin J., Gicquel, Olivier, and Parente, Alessandro. Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches.  United States: N. p., 2016. 
Web.  doi:10.1016/j.combustflame.2016.03.021.

Copy to clipboard


                    Coussement, Axel, Isaac, Benjamin J., Gicquel, Olivier, & Parente, Alessandro. Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches.  United States.  https://doi.org/10.1016/j.combustflame.2016.03.021

Copy to clipboard


                    Coussement, Axel, Isaac, Benjamin J., Gicquel, Olivier, and Parente, Alessandro. Wed .  
"Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches".  United States.  https://doi.org/10.1016/j.combustflame.2016.03.021.

Copy to clipboard


                    
@article{osti_1324341,

  title        = {Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches},

  author       = {Coussement, Axel and Isaac, Benjamin J. and Gicquel, Olivier and Parente, Alessandro},

  abstractNote = {},

  doi          = {10.1016/j.combustflame.2016.03.021},

  journal      = {Combustion and Flame},

  number       = C,

  volume       = 168,

  place        = {United States},

  year         = {2016},

  month        = {6}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (Publisher)

Publisher's Version of Record
https://doi.org/10.1016/j.combustflame.2016.03.021

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 20 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

APPLICATIONS OF CLUSTER ANALYSIS (CLA) AND PRINCIPAL COMPONENT ANALYSIS (PCA) IN FEED STRUCTURE AND FEED MOLECULAR CHEMISTRY RESEARCH, USING SYNCHROTRON-BASED FTIR MICROSPECTROSCOPY.

Journal Article YU, P - LANGMUIR

No abstract prepared.
A change-point principal component analysis (CP/PCA) method for predicting energy usage in commercial buildings: The PCA Model

Journal Article Ruch, D ; Chen, Lu ; Haberl, J S ; ... - Journal of Solar Energy Engineering; (United States)

A new method for predicting daily whole-building electricity usage in a commercial building has been developed. This method utilizes a Principal Component Analysis (PCA) of intercorrelated influencing parameters (e.g., dry-bulb temperature, solar radiation and humidity) to predict electricity consumption in conjunction with a change-point model. This paper describes the PCA procedure and presents the results of its application in conjunction with a change-point regression, to predict whole-building electricity consumption for a commercial grocery store. Comparison of the results with a traditional Multiple Linear Regression (MLR) analysis indicates that a change-point, Principal Component Analysis (CP/PCA) appears to produce a more reliablemore »« less
https://doi.org/10.1115/1.2930035
Application of Principal Components Analysis (PCA) for long-term assessment of operating releases from the nuclear power industry

Technical Report Dickerson, M H ; Walton, J J ; Tuerpe, D R

The application of the Principal Components Analysis (PCA) methodology to the long-term assessment of operating releases from the nuclear power industry was investigated. Gaussian calculations had been previously compared with MATHEW/ADPIC calculations for a simulated 24-hr release in the Hudson River Valley and an area in the southeast. Considerable differences were noted in the comparisons, which were attributed to the more realistic simulation of the time and space varying wind fields by the MATHEW/ADPIC computer codes.
https://doi.org/10.2172/6594945

Full Text Available
Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states

Journal Article Eckert-Gallup, Aubrey C. ; Sallaberry, Cédric J. ; Dallman, Ann R. ; ... - Ocean Engineering

Abstract not provided.
Cited by 50
https://doi.org/10.1016/j.oceaneng.2015.12.018

Full Text Available
Principal Component Analysis (PCA) unravels spectral components present in XPS spectra of complex oxide films on iron foil

Journal Article Fairley, Neal ; Bargiela, Pascal ; Huang, Wei-Min ; ... - Applied Surface Science Advances
https://doi.org/10.1016/j.apsadv.2023.100447

Similar Records