Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Mohd Shoaib Khan"'
Autor:
Mohd Shoaib Khan, QM Danish Lohani
Publikováno v:
Journal of Inequalities and Applications, Vol 2017, Iss 1, Pp 1-14 (2017)
Abstract In the field of pattern recognition, clustering groups the data into different clusters on the basis of similarity among them. Many a time, the similarity level between data points is derived through a distance measure; so, a number of clust
Externí odkaz:
https://doaj.org/article/1c631218bafa4046a8a28be6185b141b
Publikováno v:
Journal of Inequalities and Applications, Vol 2017, Iss 1, Pp 1-12 (2017)
Abstract Distance measures play a central role in evolving the clustering technique. Due to the rich mathematical background and natural implementation of l p $l_{p}$ distance measures, researchers were motivated to use them in almost every clusterin
Externí odkaz:
https://doaj.org/article/43c166b3025f423f8c42b26e5fd69b43
Publikováno v:
Frontiers in Molecular Biosciences, Vol 11 (2024)
Neisseria gonorrhoeae is the causative agent of the sexually transmitted disease gonorrhea. The increasing prevalence of this disease worldwide, the rise of antibiotic-resistant strains, and the difficulties in treatment necessitate the development o
Externí odkaz:
https://doaj.org/article/b04f9b7a24344bc7a67d1c3779f8ec54
Publikováno v:
Current Topics in Medicinal Chemistry. 22:1692-1727
Background: The lengthy and expensive process of developing a novel medicine often takes many years and entails a significant financial burden due to its poor success rate. Furthermore, the processing and analysis of quickly expanding massive data ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b4db4ceafe5c98382011b13523d0630
https://doi.org/10.2174/1568026622666220701091339
https://doi.org/10.2174/1568026622666220701091339
Publikováno v:
Journal of Inequalities and Special Functions. 13:1-13
In machine learning, distance measure plays an important role in defining the similarity between two data-items. In the paper, we discuss some of the drawbacks of distance measures (metrics) with their possibly induced clustering algorithms. Further,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8df807e95a77d562c1a532c34bb61161
https://doi.org/10.54379/jiasf-2022-1-1
https://doi.org/10.54379/jiasf-2022-1-1
The induced aggregation operator from the intuitionistic additive definite integral is an important tool to aggregate information. But, before utilizing any measure, it is essential to examine their existence over the given dataset . In this paper, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be0b313a614905cd0cf3f7f96036b933
https://doi.org/10.21203/rs.3.rs-1221865/v1
https://doi.org/10.21203/rs.3.rs-1221865/v1
Publikováno v:
Soft Computing. 25:9139-9161
Distance measures are among the most studied phenomena for deciding the degree of belongingness between the two distinct objects. This paper presents a new distance measure among intuitionistic fuzzy sets (IFSs) using the generalized difference seque
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d51bcaa97f70214bc621d96b5811c8f7
https://doi.org/10.1007/s00500-021-05875-2
https://doi.org/10.1007/s00500-021-05875-2
Autor:
Mohd Shoaib Khan, Q.M. Danish Lohani
Publikováno v:
Engineering Applications of Artificial Intelligence. 116:105415
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f3f57454a63d3772ae5ab75e1fb635e
https://doi.org/10.1016/j.engappai.2022.105415
https://doi.org/10.1016/j.engappai.2022.105415
Publikováno v:
FUZZ-IEEE
Atanassov came up with an idea of the intuitionistic fuzzy set (AIFS), primarily a generalized extension of Zadeh's fuzzy set. AIFS is more supple in tackling the real world's unpredictability rather than Zadeh's fuzzy set. The researchers from vario
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f77c4801ea7dc5c11aae37078917e335
https://doi.org/10.1109/fuzz45933.2021.9494450
https://doi.org/10.1109/fuzz45933.2021.9494450