Literature DB >> 18645646

Self Organising Maps for distinguishing polymer groups using thermal response curves obtained by dynamic mechanical analysis.

Gavin R Lloyd1, Richard G Brereton, John C Duncan.   

Abstract

Self Organising Maps are described including the U-Matrix, component planes, hit histograms, quality indicators as mean quantisation error and topological error. Software was written in Matlab and several new approaches for visualising multiclass maps are employed. The method is applied to a dataset consisting of the Dynamic Mechanical Analysis of 293 polymers, involving heating the polymers over a temperature range of -51 degrees C to 270 degrees C. These can be characterised in three different ways (a) amorphous or semi-crystalline (b) as 9 groups (c) as 30 grades.

Entities:  

Year:  2008        PMID: 18645646     DOI: 10.1039/b715390b

Source DB:  PubMed          Journal:  Analyst        ISSN: 0003-2654            Impact factor:   4.616


  4 in total

1.  Visualizing Intrapopulation Hematopoietic Cell Heterogeneity with Self-Organizing Maps of SIMS Data.

Authors:  Vahid Mirshafiee; Brendan A C Harley; Mary L Kraft
Journal:  Tissue Eng Part C Methods       Date:  2018-05-07       Impact factor: 3.056

2.  Self organising maps for visualising and modelling.

Authors:  Richard G Brereton
Journal:  Chem Cent J       Date:  2012-05-02       Impact factor: 4.215

3.  Self-organising maps and correlation analysis as a tool to explore patterns in excitation-emission matrix data sets and to discriminate dissolved organic matter fluorescence components.

Authors:  Elisabet Ejarque-Gonzalez; Andrea Butturini
Journal:  PLoS One       Date:  2014-06-06       Impact factor: 3.240

4.  An Artificial Neural Network Model for Assessing Frailty-Associated Factors in the Thai Population.

Authors:  Nawapong Chumha; Sujitra Funsueb; Sila Kittiwachana; Pimonpan Rattanapattanakul; Peerasak Lerttrakarnnon
Journal:  Int J Environ Res Public Health       Date:  2020-09-18       Impact factor: 3.390

  4 in total

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