A novel hesitant fuzzy tensor-based group decision-making approach with application to heterogeneous wireless network evaluation. [PDF]
Bilal M, Lucian-Popa I.
europepmc +1 more source
Abstract Many theories of human information behavior (HIB) assume that information objects are in text document format. This paper argues four important HIB theories are insufficient for describing users' search strategies for data because of assumptions about the attributes of objects that users seek.
Anthony J. Million +3 more
wiley +1 more source
A 2-dimension linguistic Pythagorean fuzzy decision-making method with application to unmanned aerial vehicle contribution assessment. [PDF]
Gao F, He W.
europepmc +1 more source
Multi-fuzzy set similarity measures using S and T operations
Priyanka Priyanka +6 more
openalex +2 more sources
Abstract This paper tackles the problem of robust and accurate fixed‐time tracking in human–robot interaction and deals with uncertainties. This work introduces a control approach for a wearable exoskeleton designed specifically for rehabilitation tasks.
Mahmoud Abdallah +4 more
wiley +1 more source
Energy-efficient scheduling of AGV-assisted robotic flexible flowshops under learning and processing time uncertainty. [PDF]
Dehnavi S, Mokhtari H, Rezvan MT.
europepmc +1 more source
Modeling and parameter estimation for fractional large‐scale interconnected Hammerstein systems
Abstract This paper addresses the challenge of modeling and identifying large‐scale interconnected systems exhibiting memory effects, hereditary properties, and non‐local interactions. We propose a fractional‐order extension of the Hammerstein architecture that incorporates Grünwald–Letnikov operators to capture complex dynamics through multiple ...
Mourad Elloumi +2 more
wiley +1 more source
Smart system for forecasting financial outcomes and supporting strategic choices. [PDF]
Lang F, Liu Y.
europepmc +1 more source
New Operations Over Interval Valued Intuitionistic Hesitant Fuzzy Set
Said Broumi, Florentín Smarandache
openalex +1 more source
Generative Deep Learning for Advanced Battery Materials
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal +3 more
wiley +1 more source

