Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Tribhuvan Singh"'
Publikováno v:
Sensors, Vol 21, Iss 12, p 4086 (2021)
A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers. Besides, due to weak exploration capability, it is easily stuck at local
Externí odkaz:
https://doaj.org/article/bb3fd51af86e4c3e92b5d4f645ff51ee
Autor:
Tribhuvan Singh
Publikováno v:
Applied Intelligence. 52:15325-15344
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75c7e64a6810efde253e3e9cef6d87dd
https://doi.org/10.1007/s10489-022-03179-y
https://doi.org/10.1007/s10489-022-03179-y
Autor:
Amita Baranwal, Tribhuvan Singh
Publikováno v:
JOURNAL OF SCIENTIFIC RESEARCH. 66:316-329
It is known that the performance of a control chart is affected by the parameter estimation adversely, in comparison to known parameter case. However, it has been showed by several authors that the large Phase I sample is required for the chart with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cadb9043d11397fa20e85008c5c4cdda
https://doi.org/10.37398/jsr.2022.660337
https://doi.org/10.37398/jsr.2022.660337
Autor:
Tribhuvan Singh, Nitin Saxena
Publikováno v:
Pattern Analysis and Applications. 24:1303-1317
Data clustering is a prevalent problem that belongs to the data mining domain. It aims to partition the given data objects into some specified number of clusters based on the sum of the intra-cluster distances. It is an NP-hard problem, and many heur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82c47c8ecc6d08f1de82560be11ea92b
https://doi.org/10.1007/s10044-021-00964-2
https://doi.org/10.1007/s10044-021-00964-2
Autor:
Tribhuvan Singh
Publikováno v:
Neural Computing and Applications. 32:17789-17803
Data clustering is one of the important techniques of data mining that is responsible for dividing N data objects into K clusters while minimizing the sum of intra-cluster distances and maximizing the sum of inter-cluster distances. Due to nonlinear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f882802902b1f437b1f60fc0d0088ba
https://doi.org/10.1007/s00521-020-04951-2
https://doi.org/10.1007/s00521-020-04951-2
Time between events (TBE) control charts play an important role in monitoring high-yield processes. In this article, Phase II Shewhart-type tr-charts, with various runs rules, are considered for monitoring TBE exponential data with a known rate param
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e33a2d3a843309499ab3dee68e3c2583
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing.
Data clustering is a crucial machine learning technique that helps divide a given dataset into many similar data objects where the data members resemble each other. It is an unsupervised learning algorithm and is hugely applied in different machine l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8789cfacd201813c775a6f39a494bab5
https://doi.org/10.1007/s12652-021-03600-3
https://doi.org/10.1007/s12652-021-03600-3
Autor:
Tribhuvan Singh
Publikováno v:
Expert Systems. 39
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e3642d027aa0a06f994a524b8aa2b51
https://doi.org/10.1111/exsy.12890
https://doi.org/10.1111/exsy.12890
Publikováno v:
Evolutionary Intelligence. 12:305-319
Environmental adaptation method is one of the evolutionary algorithms for solving single objective optimization problems. Although the algorithm converges very fast and produces diversified solutions, there are three weaknesses in it. In this paper,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6dc36113efc19d92ec024de2d1bc3860
https://doi.org/10.1007/s12065-019-00232-7
https://doi.org/10.1007/s12065-019-00232-7
Autor:
Mohamed Abdalla, Hammam A. Alshazly, Nitin Saxena, Manju Khurana, Tribhuvan Singh, Dilbag Singh
Publikováno v:
Sensors (Basel, Switzerland)
Sensors, Vol 21, Iss 4086, p 4086 (2021)
Sensors
Volume 21
Issue 12
Sensors, Vol 21, Iss 4086, p 4086 (2021)
Sensors
Volume 21
Issue 12
A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers. Besides, due to weak exploration capability, it is easily stuck at local
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71104694849a1217bbd89c5c7c278c5d
https://pubmed.ncbi.nlm.nih.gov/34198501
https://pubmed.ncbi.nlm.nih.gov/34198501