Temat: fuzzy clustering - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A new heuristic possibilistic clustering algorithm for feature selection
Autorzy:: Kacprzyk, J.
Owsinski, J. W.
Viattchenin, D. A.
Powiązania:: https://bibliotekanauki.pl/articles/384599.pdf
Data publikacji:: 2014
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: feature selection
fuzzy correlation measure
possibilistic clustering
heuristic possibilistic clustering
fuzzy cluster
Opis:: The paper deals with the problem of selection of the most informative features. A new effective and efficient heuristic possibilistic clustering algorithm for feature selection is proposed. First, a brief description of basic concepts of the heuristic approach to possibilistic clustering is provided. A technique of initial data preprocessing is described and a fuzzy correlation measure is considered. The new algorithm is described and then illustrated on the well-known Iris data set benchmark and the results obtained are compared with those by using the conventional, well-known and widely employed method of principal component analysis (PCA). Conclusions and suggestions for future research are given.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2014, 8, 2; 40-46
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: New developments in fuzzy clustering with emphasis on special types of tasks
Autorzy:: Viattchenin, D. A.
Owsiński, J. W.
Kacprzyk, J.
Powiązania:: https://bibliotekanauki.pl/articles/206677.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: clustering
fuzzy sets
possibilistic clustering
inference
three-way clustering
feature selection
Opis:: The paper is devoted to a survey of work done in fuzzy clustering, mainly during the ﬁrst decade of the 21st century, and that with emphasis on various approachesto the problem, as well as various formulations of the very problem. That is why not only the classical formulations are treated, but several other problems, related to (the use of) clustering, like feature selection, inference systems, three-way clustering, and, on the other hand, such formulations of clustering as the possibilistic one or the one involving intuitionistic fuzzy sets. These are treated as the background for presentation of some speciﬁc ideas of the main author, concerning deﬁnite heuristic algorithms for eﬀective solving of some of these problems.
Źródło:: Control and Cybernetics; 2018, 47, 2; 115-130
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Automatic generation of fuzzy inference systems using heuristic possibilistic clustering
Autorzy:: Viattchenin, D. A.
Powiązania:: https://bibliotekanauki.pl/articles/384377.pdf
Data publikacji:: 2010
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: possibilistic clustering
fuzzy cluster
typical point
tolerance threshold
fuzzy rule
Opis:: The interpretability and flexibility of fuzzy classification rules make them a popular basis for fuzzy controllers. Fuzzy control methods constitute a part of the areas of automation and robotics. The paper deals with the method of extracting fuzzy classification rules based on a heuristic method of possibilistic clustering. The description of basic concepts of the heuristic method of possibilistic clustering based on the allotment concept is provided. A general plan of the D-AFC(c)-algorithm is also given. A method of constructing and tuning of fuzzy rules based on clustering results is proposed. An illustrative example of the method's application to the Anderson's Iris data is carried out. An analysis of the experimental results is given and preliminary conclusions are formulated.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 3; 36-44
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 4.

Tytuł:: Extracting fuzzy classifications rules from three - way data
Autorzy:: Kacprzyk, J.
Owsinski, J. W.
Viattchenin, D. A.
Powiązania:: https://bibliotekanauki.pl/articles/385102.pdf
Data publikacji:: 2014
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: three-way data
possibilistic clustering
fuzzy cluster
typical point
fuzzy rule
Opis:: The paper deals in the conceptual way with the problem of extracting fuzzy classification rules from the three-way data meant in the sense of Sato and Sato [7]. A novel technique based on a heuristic method of possibilistic clustering is proposed. A description of basic concepts of a heuristic method of possibilistic clustering based on concept of an allotment is provided. A preprocessing technique for three-way data is shown. An extended method of constructing fuzzy classification rules based on clustering results is proposed. An illustrative example of the method’s application to the Sato and Sato’s data [7] is provided. An analysis of the experimental results obtained with some conclusions are given.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2014, 8, 2; 47-57
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 5.

Tytuł:: A Method for Estimating the Least Number of Objects in Fuzzy Clusters
Autorzy:: Viattchenin, D. A.
Yaroma, A.
Powiązania:: https://bibliotekanauki.pl/articles/226222.pdf
Data publikacji:: 2017
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: possibilistic clustering
fuzzy cluster
allotment
cluster size
Opis:: The theoretical note deals with the problem of estimation of the value of the least number of objects in fuzzy clusters for following detection of the optimal number of objects in fuzzy clusters through heuristic possibilistic clustering. A technique for detecting the optimal maximal number of elements in the a priori unknown number of fuzzy clusters of the sought clustering structure is reminded and a procedure for finding the initial minimal value of the number of objects in fuzzy clusters is proposed. Numerical examples are considered and conclusions are formulated.
Źródło:: International Journal of Electronics and Telecommunications; 2017, 63, 4; 341-346
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

Artykuł

Informacja