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Naslov:Maximal product-based intuitionistic fuzzy line graphs for healthcare predictive analysis
Avtorji:ID Meenakshi, Annamalai (Avtor)
ID Mishra, J. Shivangi (Avtor)
ID Mršić, Leo (Avtor)
ID Kalampakas, Antonios (Avtor)
ID Samanta, Sovan (Avtor)
ID Allahviranloo, Tofigh (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://www.sciencedirect.com/science/article/pii/S209044792500680X?via%3Dihub
 
.pdf PDF - Predstavitvena datoteka, prenos (3,20 MB)
MD5: FD39C53964433C1E411AFCE6EC2C230F
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo RUDOLFOVO - Rudolfovo – Znanstveno in tehnološko središče Novo mesto
Povzetek:This paper explores the applications of Intuitionistic Fuzzy Graphs (ℐ ℱ � ) representing uncertainty and impre cision in complex systems through the analysis of correlation and regression coefficients (� ℛ� �) with focus on the maximal product. The study examines the relationships between the edges of the graph by analysing the line graph derived from ℐ ℱ � , facilitating a deeper understanding of the network’s dynamics. The construction of adjacency matrices that incorporate both membership and non-membership values enables the calculation of energy and weight scores, quantifying the strength and predictive correlations among variables. Furthermore, the study discusses the complement of Intuitionistic Fuzzy Line Graphs (ℐ ℱ ℒ � ), using maximal product anal ysis to uncover concealed relationships within the network. MATLAB is used to generate heatmaps that visually represent the importance of correlation to critical network characteristics. The practical importance is demon strated in a healthcare context, particularly in predicting diabetes risk by modelling factors of glucose levels, body mass index (BMI), and insulin. Heatmaps can be effectively visualized to show interrelationships between these features, aiding in the interpretation of network patterns.
Ključne besede:intuitionistic fuzzy graphs, intuitionistic fuzzy line graphs, maximal product, adjacency matrices, correlation and regression coefficients
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Datum objave:07.01.2026
Založnik:Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University
Leto izida:2026
Št. strani:str. 1-12
Številčenje:Vol. 17, iss. 1, art. 103939
PID:20.500.12556/DiRROS-27390 Novo okno
UDK:519.17
ISSN pri članku:2090-4495
DOI:10.1016/j.asej.2025.103939 Novo okno
COBISS.SI-ID:266357251 Novo okno
Avtorske pravice:© 2025 The Author(s).
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 27. 1. 2026; Soavtorji: J. Shivangi Mishra, Leo Mršić, Antonios Kalampakas, Sovan Samanta, Tofigh Allahviranloo;
Datum objave v DiRROS:04.02.2026
Število ogledov:39
Število prenosov:16
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Ain Shams Engineering Journal
Skrajšan naslov:Ain Shams Eng. J.
Založnik:Ain Shams University, Faculty of Engineering, Elsevier
ISSN:2090-4495
COBISS.SI-ID:68370435 Novo okno

Licence

Licenca:CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
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