Qualitative identification of clinkers by fuzzy clustering

Fuzzy clustering of trace elements of clinkers
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Updated 7 Jul 2014

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With the application of this code fuzzy classifier is identified by unsupervised fuzzy clustering. The most relevant trace elements were selected based on the obtained clusters by the modified version of Fisher interclass separability method. The classification of Portuguese and South African clinkers is used as an illustrative example. The results show that the proposed method is useful to identify compact classifiers that are able to determine the origin of the clinker; and the obtained classifier is easy to use and interpret for engineers and researchers, even when they are not familiar with the concept of fuzzy logic.

The algorithm is also described in:
J. Madár, J. Abonyi, F. Szeifert, Feedback linearizing control using hybrid neural networks identified by sensitivity approach, Engineering Applications of Artificial Intelligence, 343-351, 2005
(It is in the .zip file)

More MATLAB implementation on my website:
http://www.abonyilab.com/software-and-data

Cite As

Janos Abonyi (2024). Qualitative identification of clinkers by fuzzy clustering (https://www.mathworks.com/matlabcentral/fileexchange/47162-qualitative-identification-of-clinkers-by-fuzzy-clustering), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R14SP1
Compatible with any release
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Version Published Release Notes
1.0.0.0