Results 31 to 40 of about 12,223,733 (321)

Distance and Similarity Measures of Intuitionistic Fuzzy Parameterized Intuitionistic Fuzzy Soft Matrices and Their Applications to Data Classification in Supervised Learning

open access: yesAxioms, 2023
Intuitionistic fuzzy parameterized intuitionistic fuzzy soft matrices (ifpifs-matrices), proposed by Enginoğlu and Arslan in 2020, are worth utilizing in data classification in supervised learning due to coming into prominence with their ability to model
Samet Memiş   +4 more
doaj   +1 more source

On some distance measures of complex Pythagorean fuzzy sets and their applications in pattern recognition

open access: yesComplex & Intelligent Systems, 2019
The concept of complex fuzzy set (CFS) and complex intuitionistic fuzzy set (CIFS) is two recent developments in the field of fuzzy set (FS) theory. The significance of these concepts lies in the fact that these concepts assigned membership grades from ...
Kifayat Ullah   +3 more
semanticscholar   +1 more source

Detecting Patterns of Infection-Induced Fertility Using Fermatean Neutrosophic Set With Similarity Analysis

open access: yesIEEE Access, 2023
Urinary tract infections ( $\mathbb {UTI}s$ ) pose a significant challenge globally, as they increase the risk of miscarriage and promote the growth of gram-negative bacteria.
Muhammad Saeed   +4 more
doaj   +1 more source

A Neutrosophic Cubic Hesitant Fuzzy Decision Support System, Application in the Diagnosis and Grading of Prostate Cancer

open access: yesFractal and Fractional, 2022
According to available estimates with WHO, cancers are the sixth leading cause of global human morbidity and mortality. Prostate Cancer is the fifth-ranked most lethal among various cancers, and hence it warrants serious, dedicated research for improving
Joseph David Madasi   +5 more
doaj   +1 more source

Different distance measures for fuzzy linear regression with Monte Carlo methods [PDF]

open access: yes, 2016
The aim of this study was to determine the best distance measure for estimating the fuzzy linear regression model parameters with Monte Carlo (MC) methods.
Cattaneo, Marco E.G.V., İçen, Duygu
core   +2 more sources

Fuzzy Based Convolutional Noise Clustering Classifier to Handle the Noise and Heterogeneity in Image Classification

open access: yesMathematics, 2022
Conventional Noise Clustering (NC) algorithms do not consider any spatial information in the image. In this study, three algorithms have been presented, Noise Local Information c-means (NLICM) and Adaptive Noise Local Information c-Means (ADNLICM), which
Shilpa Suman, Dheeraj Kumar, Anil Kumar
doaj   +1 more source

Time series classification with ensembles of elastic distance measures [PDF]

open access: yes, 2015
Several alternative distance measures for comparing time series have recently been proposed and evaluated on time series classification (TSC) problems.
A Stefan   +14 more
core   +1 more source

The Cubic Bipolar Neutrosophic Sets theory and Uncertainty Management in Environmental Data Analysis [PDF]

open access: yesNeutrosophic Sets and Systems
Environmental data analysis often faces uncertainties in measurements. Cubic Bipolar Neutrosophic Sets (CBN Sets) provide a powerful framework to address this challenge.
A.Salama   +2 more
doaj   +1 more source

Some cosine similarity measures and distance measures between q‐rung orthopair fuzzy sets

open access: yesInternational Journal of Intelligent Systems, 2019
In this paper, we consider some cosine similarity measures and distance measures between q‐rung orthopair fuzzy sets (q‐ROFSs). First, we define a cosine similarity measure and a Euclidean distance measure of q‐ROFSs, their properties are also studied ...
Donghai Liu, Xiao-hong Chen, Dan Peng
semanticscholar   +1 more source

Distance measures to compare real and ideal quantum processes [PDF]

open access: yes, 2004
With growing success in experimental implementations it is critical to identify a "gold standard" for quantum information processing, a single measure of distance that can be used to compare and contrast different experiments.
A. M. Childs   +6 more
core   +2 more sources

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