Fuzzy Clustering Data Arrays with Omitted Observations

Публікація:
Fuzzy Clustering Data Arrays with Omitted Observations

dc.contributor.author	Женбинг, Х.
dc.contributor.author	Бодянский, Е. В.
dc.contributor.author	Тыщенко, А. К.
dc.contributor.author	Ткачев, В. Н.
dc.date.accessioned	2018-04-11T06:35:13Z
dc.date.available	2018-04-11T06:35:13Z
dc.date.issued	2017
dc.description.abstract	An adaptive neural system which solves a problem of clustering data with missing values in an online mode with a permanent correction of restorable table elements and clusters’ centroids is proposed in this article. The introduced neural system is characterized by both a high speed and a simple numerical implementation. It can process information in a real-time mode.	uk_UA
dc.identifier.citation	Zhengbing H. Fuzzy Clustering Data Arrays with Omitted Observations / H. Zhengbing, Ye. Bodyanskiy, O. Tyshchenko, V. Tkachov / I.J. Intelligent Systems and Applications, v.9, # 7, 2017 – P. 24-33.	uk_UA
dc.identifier.issn	2074-904X
dc.identifier.issn	2074-9058
dc.identifier.uri	http://openarchive.nure.ua/handle/document/4726
dc.language.iso	en	uk_UA
dc.subject	computational complexity	uk_UA
dc.subject	fuzzy clustering	uk_UA
dc.subject	recovery	uk_UA
dc.subject	missing values	uk_UA
dc.title	Fuzzy Clustering Data Arrays with Omitted Observations	uk_UA
dspace.entity.type	Publication