Zobrazeno 1 - 10
of 4 315
pro vyhledávání: '"Meta-Heuristics"'
Autor:
Abhijit Saha
Publikováno v:
Discover Geoscience, Vol 2, Iss 1, Pp 1-23 (2024)
Abstract The use of nature-inspired meta-heuristics to tackle complex optimization problems is steadily gaining popularity within a rapidly evolving world. Swarm intelligence (SI) optimization motivated by behavior of community-based organisms of flo
Externí odkaz:
https://doaj.org/article/a9b5ace4c23d4cd98c5425a1e7737e46
Publikováno v:
Alexandria Engineering Journal, Vol 104, Iss , Pp 171-192 (2024)
Fraud detection in banking systems is crucial for financial stability, customer protection, reputation management, and regulatory compliance. Machine Learning (ML) is vital in improving data analysis, real-time fraud detection, and developing fraud t
Externí odkaz:
https://doaj.org/article/aaa78269fdc941e3923c5dab5ee9057b
Publikováno v:
Management Decision, 2024, Vol. 62, Issue 13, pp. 283-308.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/MD-06-2023-1073
Publikováno v:
BizInfo, Vol 15, Iss 1, Pp 1-10 (2024)
Today, the algorithm selection paradigm has become one of the promising approaches in the field of optimization problems. Its main goal is to solve each case of an optimization problem with the most accurate algorithm using machine learning technique
Externí odkaz:
https://doaj.org/article/224f89cf11ec48dfaa6766e8c61b9d9d
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-27 (2024)
Abstract As a preprocessing for machine learning and data mining, Feature Selection plays an important role. Feature selection aims to streamline high-dimensional data by eliminating irrelevant and redundant features, which reduces the potential curs
Externí odkaz:
https://doaj.org/article/995bf19c4b53474eb00649525ce0f190
Autor:
Priteesha Sarangi, Prabhujit Mohapatra
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-26 (2024)
Abstract The Mountain Gazelle Optimizer (MGO) algorithm has become one of the most prominent swarm-inspired meta-heuristic algorithms because of its outstanding rapid convergence and excellent accuracy. However, the MGO still faces premature converge
Externí odkaz:
https://doaj.org/article/1d8e88e87ae64e8698d64bc365baeced
Autor:
Mohd Helmi Suid, Mohd Ashraf Ahmad, Ahmad Nor Kasruddin Nasir, Mohd Riduwan Ghazali, Julakha Jahan Jui
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102506- (2024)
The widespread use of dynamic systems has greatly simplified various human-operated tasks. However, the complex and nonlinear nature of these systems has posed challenges in determining their structure due to heavy reliance on modeling for theoretica
Externí odkaz:
https://doaj.org/article/e149ebd01866401a9bf973bb80952db8
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
IntroductionFuel cell technology is a harbinger of the future for generating electricity due to their high efficiency and low emissions achieved through the direct conversion of chemical energy into electrical energy without combustion.MethodsTo opti
Externí odkaz:
https://doaj.org/article/1b7cb22b844f469ca54b13da2e0dc6cf
Autor:
Sundaram B. Pandya, Kanak Kalita, Robert Čep, Pradeep Jangir, Jasgurpreet Singh Chohan, Laith Abualigah
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-30 (2024)
Abstract This study delves into the exploration of a novel Multi-objective Snow Ablation Optimizer (MOSAO) algorithm, tailored for addressing expansive Optimal Power Flow (OPF) challenges inherent in intricate power systems. These systems are often c
Externí odkaz:
https://doaj.org/article/0b9fbfa5d20341e8bf7d6072e0f83e1d
Autor:
Ahmed Almutairi, Mahmoud Owais
Publikováno v:
IEEE Access, Vol 12, Pp 180385-180403 (2024)
Over time, traffic sensors have become recognized as a leading source of traffic flow data. Despite their solid capabilities for measuring various types of traffic flow information, they cannot be implemented at all intersections or mid-blocks within
Externí odkaz:
https://doaj.org/article/22d65904c3a94b41845cab0118e028c0