Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Guzel Shkaberina"'
Autor:
Igor Masich, Natalya Rezova, Guzel Shkaberina, Sergei Mironov, Mariya Bartosh, Lev Kazakovtsev
Publikováno v:
Algorithms, Vol 16, Iss 5, p 246 (2023)
A number of real-world problems of automatic grouping of objects or clustering require a reasonable solution and the possibility of interpreting the result. More specific is the problem of identifying homogeneous subgroups of objects. The number of g
Externí odkaz:
https://doaj.org/article/560cede863b14a709f61879b62b1106a
Publikováno v:
Algorithms, Vol 16, Iss 1, p 5 (2022)
Finding the cluster structure is essential for analyzing self-organized networking structures, such as social networks. In such problems, a wide variety of distance measures can be used. Common clustering methods often require the number of clusters
Externí odkaz:
https://doaj.org/article/dbca7ead568547e3afc0db2d0efbc224
Autor:
Vukašin Stanojević, Lev Kazakovtsev, Predrag S. Stanimirović, Natalya Rezova, Guzel Shkaberina
Publikováno v:
Algorithms, Vol 15, Iss 10, p 348 (2022)
In this work, we consider the problem of calculating the generalized Moore–Penrose inverse, which is essential in many applications of graph theory. We propose an algorithm for the massively parallel systems based on the recursive algorithm for the
Externí odkaz:
https://doaj.org/article/8d9d822291a845f08abfd8a35034fe0f
Publikováno v:
Algorithms, Vol 15, Iss 6, p 191 (2022)
Automatic grouping (clustering) involves dividing a set of objects into subsets (groups) so that the objects from one subset are more similar to each other than to the objects from other subsets according to some criterion. Kohonen neural networks ar
Externí odkaz:
https://doaj.org/article/74f7e9e9a2f44a398e62363fbe1bef43
Publikováno v:
Algorithms, Vol 14, Iss 5, p 130 (2021)
The continuous p-median problem (CPMP) is one of the most popular and widely used models in location theory that minimizes the sum of distances from known demand points to the sought points called centers or medians. This NP-hard location problem is
Externí odkaz:
https://doaj.org/article/6518e819f2fd44eca76bde9c0b183fde
Publikováno v:
VII INTERNATIONAL CONFERENCE “SAFETY PROBLEMS OF CIVIL ENGINEERING CRITICAL INFRASTRUCTURES” (SPCECI2021).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30056fbd587ddf9ed02460f8b50b87b7
https://doi.org/10.1063/5.0124953
https://doi.org/10.1063/5.0124953
Publikováno v:
2022 International Conference on Information Technologies (InfoTech).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0119e6cf1f847b814b88016b54757222
https://doi.org/10.1109/infotech55606.2022.9897105
https://doi.org/10.1109/infotech55606.2022.9897105
Autor:
Guzel Shkaberina, Lev A. Kazakovtsev
Publikováno v:
Industrial Engineering & Management Systems. 19:901-907
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d1b38e2820ef68f4a36956e6aeeec08
https://doi.org/10.7232/iems.2020.19.4.901
https://doi.org/10.7232/iems.2020.19.4.901
Publikováno v:
Mathematical Problems in Engineering, Vol 2020 (2020)
The k-means problem is one of the most popular models of cluster analysis. The problem is NP-hard, and modern literature offers many competing heuristic approaches. Sometimes practical problems require obtaining such a result (albeit notExact), withi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f7c2220474acbc4173079e36dbf6d59
https://doi.org/10.1155/2020/8839763
https://doi.org/10.1155/2020/8839763
Autor:
Lev Kazakovtsev, Predrag S. Stanimirović, Guzel Shkaberina, Natalya Rezova, Vukašin Stanojević
Publikováno v:
Algorithms; Volume 15; Issue 10; Pages: 348
In this work, we consider the problem of calculating the generalized Moore–Penrose inverse, which is essential in many applications of graph theory. We propose an algorithm for the massively parallel systems based on the recursive algorithm for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01051158294417d92490146e20e87d6d
https://doi.org/10.3390/a15100348
https://doi.org/10.3390/a15100348