A literature review and critical analysis of metaheuristics recently developed
Metaheuristic algorithms have applicability in various fields where it is necessary to solve
optimization problems. It has been a common practice in this field for several years to …
optimization problems. It has been a common practice in this field for several years to …
Advances in manta ray foraging optimization: A comprehensive survey
FS Gharehchopogh, S Ghafouri, M Namazi… - Journal of Bionic …, 2024 - Springer
This paper comprehensively analyzes the Manta Ray Foraging Optimization (MRFO)
algorithm and its integration into diverse academic fields. Introduced in 2020, the MRFO …
algorithm and its integration into diverse academic fields. Introduced in 2020, the MRFO …
Efficient feature selection using weighted superposition attraction optimization algorithm
As the volume of data generated by information systems continues to increase, machine
learning (ML) techniques have become essential for the extraction of meaningful insights …
learning (ML) techniques have become essential for the extraction of meaningful insights …
Parameter extraction of photovoltaic cells and modules by hybrid white shark optimizer and artificial rabbits optimization
This study presents the parameter extraction of photovoltaic (PV) cells and modules using a
new hybrid metaheuristic algorithm developed based on the white shark optimizer (WSO) …
new hybrid metaheuristic algorithm developed based on the white shark optimizer (WSO) …
Intrusion detection in Internet of things using improved binary golden jackal optimization algorithm and LSTM
AV Hanafi, A Ghaffari, H Rezaei, A Valipour… - Cluster Computing, 2024 - Springer
Internet of things (IoT) technology has gained a reputation in recent years due to its ease of
use and adaptability. Due to the amount of sensitive and significant data exchanged over the …
use and adaptability. Due to the amount of sensitive and significant data exchanged over the …
[HTML][HTML] Golden jackal optimization algorithm with deep learning assisted intrusion detection system for network security
NO Aljehane, HA Mengash, MM Eltahir… - Alexandria Engineering …, 2024 - Elsevier
Network security is essential to our daily communications and networks. Cybersecurity
researchers initiate the significance of emerging proficient network intrusion detection …
researchers initiate the significance of emerging proficient network intrusion detection …
Feature selection for high dimensional datasets based on quantum-based dwarf mongoose optimization
Feature selection (FS) methods play essential roles in different machine learning
applications. Several FS methods have been developed; however, those FS methods that …
applications. Several FS methods have been developed; however, those FS methods that …
Optimized fuzzy K-nearest neighbor approach for accurate lung cancer prediction based on radial endobronchial ultrasonography
J Xing, C Li, P Wu, X Cai, J Ouyang - Computers in Biology and Medicine, 2024 - Elsevier
Radial endobronchial ultrasonography (R-EBUS) has been a surge in the development of
new ultrasonography for the diagnosis of pulmonary diseases beyond the central airway …
new ultrasonography for the diagnosis of pulmonary diseases beyond the central airway …
Anomaly detection for iot systems using active learning
M Zakariah, AS Almazyad - Applied Sciences, 2023 - mdpi.com
The prevalence of Internet of Things (IoT) technologies is on the rise, making the
identification of anomalies in IoT systems crucial for ensuring their security and reliability …
identification of anomalies in IoT systems crucial for ensuring their security and reliability …
BukaGini: a stability-aware Gini index feature selection algorithm for robust model performance
Feature interaction is a vital aspect of Machine Learning (ML) algorithms, and gaining a
deep understanding of these interactions can significantly enhance model performance …
deep understanding of these interactions can significantly enhance model performance …