Bald eagle search algorithm: a comprehensive review with its variants and applications
Bald Eagle Search (BES) is a recent and highly successful swarm-based metaheuristic
algorithm inspired by the hunting strategy of bald eagles in capturing prey. With its …
algorithm inspired by the hunting strategy of bald eagles in capturing prey. With its …
Artificial ecosystem-based optimization with dwarf mongoose optimization for feature selection and global optimization problems
Meta-Heuristic (MH) algorithms have recently proven successful in a broad range of
applications because of their strong capabilities in picking the optimal features and …
applications because of their strong capabilities in picking the optimal features and …
An enhanced hunter‐prey optimization for optimal power flow with FACTS devices and wind power integration
This paper proposes an improved version of the Hunter‐prey optimization (HPO) method to
enhance its search capabilities for solving the Optimal Power Flow (OPF) problem, which …
enhance its search capabilities for solving the Optimal Power Flow (OPF) problem, which …
[HTML][HTML] A quasi-oppositional learning of updating quantum state and Q-learning based on the dung beetle algorithm for global optimization
There are many tricky optimization problems in real life, and metaheuristic algorithms are the
most effective way to solve optimization problems at a lower cost. The dung beetle …
most effective way to solve optimization problems at a lower cost. The dung beetle …
A CNN-based model to count the leaves of rosette plants (LC-Net)
Plant image analysis is a significant tool for plant phenoty**. Image analysis has been
used to assess plant trails, forecast plant growth, and offer geographical information about …
used to assess plant trails, forecast plant growth, and offer geographical information about …
[HTML][HTML] PSAO: An enhanced Aquila Optimizer with particle swarm mechanism for engineering design and UAV path planning problems
S Wu, B He, J Zhang, C Chen, J Yang - Alexandria Engineering Journal, 2024 - Elsevier
Metaheuristic algorithms have become increasingly significant in solving complex
optimization problems. To address the limitations of the original Aquila Optimizer (AO), such …
optimization problems. To address the limitations of the original Aquila Optimizer (AO), such …
Multi-agent variational approach for robotics: a bio-inspired perspective
This study proposes an adaptable, bio-inspired optimization algorithm for Multi-Agent Space
Exploration. The recommended approach combines a parameterized Aquila Optimizer, a bio …
Exploration. The recommended approach combines a parameterized Aquila Optimizer, a bio …
Adapting the pre-trained convolutional neural networks to improve the anomaly detection and classification in mammographic images
Mortality from breast cancer (BC) is among the top causes of cancer death in women. BC
can be effectively treated when diagnosed early, improving the likelihood that a patient will …
can be effectively treated when diagnosed early, improving the likelihood that a patient will …
A bio-medical snake optimizer system driven by logarithmic surviving global search for optimizing feature selection and its application for disorder recognition
It is of paramount importance to enhance medical practices, given how important it is to
protect human life. Medical therapy can be accelerated by automating patient prediction …
protect human life. Medical therapy can be accelerated by automating patient prediction …
Extraction of Roads Using the Archimedes Tuning Process with the Quantum Dilated Convolutional Neural Network
Road network extraction is a significant challenge in remote sensing (RS). Automated
techniques for interpreting RS imagery offer a cost-effective solution for obtaining road …
techniques for interpreting RS imagery offer a cost-effective solution for obtaining road …