Zobrazeno 1 - 10
of 309
pro vyhledávání: '"János, Abonyi"'
Autor:
Tímea Czvetkó, János Abonyi
Publikováno v:
SoftwareX, Vol 28, Iss , Pp 101963- (2024)
HAT-VIS is a hypergraph visualization tool designed within the MATLAB environment, serving to depict the inherent relationships present within hypergraphs. The current scarcity of MATLAB tools dedicated to the analysis and visualization of hypergraph
Externí odkaz:
https://doaj.org/article/b361278dc50f402c9a86363b8177ebb4
Publikováno v:
MethodsX, Vol 13, Iss , Pp 102838- (2024)
This article focuses on improving indoor positioning data through data reconciliation. Indoor positioning systems are increasingly used for resource tracking to monitor manufacturing and warehouse processes. However, measurement errors due to noise c
Externí odkaz:
https://doaj.org/article/32c105196de4429b92cb11b83e73f6cb
Publikováno v:
Production and Manufacturing Research: An Open Access Journal, Vol 12, Iss 1 (2024)
The Operator 5.0 concept calls for the self-resilience of operators in Industry 5.0, including the cognitive aspect. Despite attempts to develop supporting technologies, achieved results are loosely connected without a comprehensive approach. Looking
Externí odkaz:
https://doaj.org/article/9c1ec31eb71a4ccca310539905e4af56
Autor:
László Gadár, János Abonyi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Identifying communities in multilayer networks is crucial for understanding the structural dynamics of complex systems. Traditional community detection algorithms often overlook the presence of overlapping edges within communities, despite t
Externí odkaz:
https://doaj.org/article/6aecc69f1cb4494ab10120e7c3cfe00c
Autor:
László Gadár, János Abonyi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract In real-world classification problems, it is important to build accurate prediction models and provide information that can improve decision-making. Decision-support tools are often based on network models, and this article uses information
Externí odkaz:
https://doaj.org/article/b89a34576ec94fc1b3e187eb1d52ee03
Autor:
Éva Kenyeres, János Abonyi
Publikováno v:
Applied Sciences, Vol 14, Iss 21, p 9652 (2024)
This study presents a model-based parameter estimation method for integrating and validating uncertainty in expert knowledge and simulation models. The parameters of the models of complex systems are often unknown due to a lack of measurement data. T
Externí odkaz:
https://doaj.org/article/daf48254684642b8903cb0219b050331
Publikováno v:
Computers, Vol 13, Iss 10, p 252 (2024)
Machine learning (ML) revolutionized traditional machine fault detection and identification (FDI), as complex-structured models with well-designed unsupervised learning strategies can detect abnormal patterns from abundant data, which significantly r
Externí odkaz:
https://doaj.org/article/fa04d4ef3bbd43a99e6eb8b24c7f538d
Publikováno v:
MethodsX, Vol 12, Iss , Pp 102535- (2024)
The analysis of event sequences with temporal dependencies holds substantial importance across various domains, including healthcare. This study introduces a novel approach that combines sequential rule mining and survival analysis to uncover signifi
Externí odkaz:
https://doaj.org/article/b0734c6dcfe440d596ea0491325f85ce
Publikováno v:
Heliyon, Vol 10, Iss 9, Pp e29764- (2024)
The parameter identification of failure models for composite plies can be cumbersome, due to multiple effects as the consequence of brittle fracture. Our work proposes an iterative, nonlinear design of experiments (DoE) approach that finds the most i
Externí odkaz:
https://doaj.org/article/43a79a8d5b384581b9ecc19362464a7a
Publikováno v:
Heliyon, Vol 10, Iss 8, Pp e29437- (2024)
This paper presents a methodology that aims to enhance the accuracy of probability density estimation in mobility pattern analysis by integrating prior knowledge of system dynamics and contextual information into the particle filter algorithm. The qu
Externí odkaz:
https://doaj.org/article/da50dee33b694bc999ead5ad4ec79a66