1996
DOI: 10.1021/ci9502717
|View full text |Cite
|
Sign up to set email alerts
|

A Fuzzy Classification of the Chemical Elements

Abstract: The fuzzy clustering algorithm is applied in order to obtain the cluster structure of the chemical elements, based on their physical, chemical, and structural properties. The results obtained with the fuzzy method are consistent with the chemical behavior of the elements and with the predictions based on their electronic structure. An IBM-PC computer has been used to run the corresponding program written in Pascal. Moreover, the results suggest some new untrivial relationships between chemical elements accordi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

1
26
0

Year Published

1997
1997
2017
2017

Publication Types

Select...
7
2

Relationship

3
6

Authors

Journals

citations
Cited by 24 publications
(27 citation statements)
references
References 28 publications
1
26
0
Order By: Relevance
“…Moreover, we are not interested only in the final fuzzy partition; we are interested in the relationships between different fuzzy sets. These relationships may be observed very well from the binary classification tree [6,7,9,11,12,14].…”
Section: Fuzzy Divisive Hierarchical Clusteringmentioning
confidence: 67%
See 1 more Smart Citation
“…Moreover, we are not interested only in the final fuzzy partition; we are interested in the relationships between different fuzzy sets. These relationships may be observed very well from the binary classification tree [6,7,9,11,12,14].…”
Section: Fuzzy Divisive Hierarchical Clusteringmentioning
confidence: 67%
“…Among other interesting applications, the fuzzy clustering theory developed in References [3,4,6,8] has been used for the selection and the optimal combination of solvents [7,13], for the classification of Roman pottery [9], for the cross-classification of Greek muds [6], for the development of a fuzzy system of chemical elements [12,14], for producing a performant fuzzy regression algorithm [10], and for the cross-classification of thin layer chromatography data [11].…”
Section: Introductionmentioning
confidence: 99%
“…In general, a fuzzy divisive hierarchical clustering algorithm with objective function can be formulated as follows [38][39][40][41][42]: let X = {x 1 , . .…”
Section: Hierarchical Fuzzy Clusteringmentioning
confidence: 99%
“…Here we propose a multivariate data analysis [8][9][10][11][12][13][14] of the amino acids, by principal components analysis (PCA) and cluster analysis (CA). PCA helps to reduce the number of variables necessary to describe a system, by maintaining the maximum possible information.…”
Section: Introductionmentioning
confidence: 99%