Sentence examples for numerical clusters from inspiring English sources

Numerical clusters effectively reflect the land use types and their change during urbanization.

From numerical clusters, and – as Ricolfi's article clearly demonstrates – from comparisons between numerical clusters one can mine information that can be used to cope with complexity rather than to forecast a future which in spite of everything remains unpredictable [59].

Grouping methods, including urban rural division, in situ vegetation type, land use types in different scales and numerical clustering, were compared for both single soil attributes and "soil set" defined by multiple variables.

In this paper, the use of γ-ray spectrometry data (i.e. potassium K, uranium U, thorium Th and total count TC), coupled with a numerical clustering algorithm (i.e. fuzzy k-means (FKM) algorithm) is explored in order to identify geological and geomorphological units at the district and soil mapping units at a broader catchment level.

Numerical clustering based on phenotypes of these gene mutants revealed that programmed cell death (PCD) is the major contributor to resistance.

For simplicity we used a numerical cluster coding for each study.

In the text, exemplary transcripts of interest are notated with their numerical cluster identifiers.

Although it employs distance function for numerical data clustering, it does not specify initial points or cluster number and it can also determine arbitrary shapes.

This paper presents studies on applying the numerical taxonomy clustering technique to software applications.

The pollen and vegetation data were analysed independently using numerical methods (clustering and correspondence analysis) to investigate how vegetation is reflected in pollen assemblages.

He became involved with R in 1995, was a founding member of the R core team in 1997 and has since been active in the development of R. His research interests include nonparametric curve estimation, numerical approximation, clustering, robust statistics, sparse matrices and statistical computing in general.