โ Scribed by Manfred Nagel; Peter Ay
No coin nor oath required. For personal study only.
The assessment or description of the internal morphology of flocs plays an important role in the optimization of flocculation processes and the development of highperformance reaction systems. This paper is focused on mathematical algorithms-namely c-means clustering, fuzzy clustering, Fourier transformation and kernel smoothing-to reconstruct the internal cluster structure of flocs. In principle, all methods are suitable to interpret the growth history of flocs. However, it is shown that at the moment c-means clustering in combination with a data preparation step seems to be the most favorable procedure in that context. A detailed description of the data preparation procedure is not part of this work.
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