Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations

D Molina, J Poyatos, JD Ser, S García, A Hussain… - Cognitive …, 2020 - Springer
In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …

Flood algorithm (FLA): an efficient inspired meta-heuristic for engineering optimization

M Ghasemi, K Golalipour, M Zare, S Mirjalili… - The Journal of …, 2024 - Springer
Introducing a novel meta-heuristic optimization algorithm, the Flood Algorithm (FLA) draws
inspiration from the intricate movement and flow patterns of water masses during flooding …

Polar fox optimization algorithm: a novel meta-heuristic algorithm

A Ghiaskar, A Amiri, S Mirjalili - Neural Computing and Applications, 2024 - Springer
The proposed paper introduces a new optimization algorithm inspired by nature called the
polar fox optimization algorithm (PFA). This algorithm addresses the herd life of polar foxes …

Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization

OR Adegboye, AK Feda, OS Ojekemi, EB Agyekum… - Scientific Reports, 2024 - nature.com
The effective meta-heuristic technique known as the grey wolf optimizer (GWO) has shown
its proficiency. However, due to its reliance on the alpha wolf for guiding the position …

Optimal extreme learning machine for diagnosing brain tumor based on modified sailfish optimizer

SA Amin, MKS Alqudah, SA Almutairi, R Almajed… - Heliyon, 2024 - cell.com
This study proposes a hierarchical automated methodology for detecting brain tumors in
Magnetic Resonance Imaging (MRI), focusing on preprocessing images to improve quality …

ICSOMPA: A novel improved hybrid algorithm for global optimisation

U Mohammed, T Karataev, O Oshiga… - Evolutionary …, 2024 - Springer
Abstract The Marine Predators Algorithm (MPA) is among the recently proposed
metaheuristic algorithms (MAs), and it got its inspiration from the ocean predators' foraging …

[HTML][HTML] Machine Learning Model for Predicting the Height of the Water-Conducting Fracture Zone Considering the Influence of Key Stratum and Dip Mining Intensity

Y Che, X Cui, Y Wang, P Li - Water, 2025 - mdpi.com
Predicting the height of the water-conducting fracture zone (WCFZ) is crucial for preventing
water inrush and ensuring safe underground mining operations. In this study, we propose a …

Enhancement in Optimal Resource-based Data Transmission over LPWAN using a Deep Adaptive Reinforcement Learning Model aided by Novel Remora with Lotus …

MR Rao, S Sundar - IEEE Access, 2024 - ieeexplore.ieee.org
Wireless Sensor Networks (WSN) are adopting low-power wide area networks (LPWAN),
such as long-range (LoRa) wide area networks, to increase communication standards. LoRa …

Optimization of process parameters for printed circuit board drilling for Micro needle with Socio inspired optimization algorithms

AS Shastri, A Nargundkar, S Silswal… - International Journal on …, 2024 - Springer
Abstract Printed Circuit Board (PCB) is the primary component for building any electrical
circuit. Electrical interconnection of PCBs is achieved through micro-holes. These holes are …

[PDF][PDF] Optimization of Welded Beam Design Problem Using Water Evaporation Optimization Algorithm

AAH Alkurdi - Academic Journal of Nawroz University, 2023 - pdfs.semanticscholar.org
This paper introduces a novel approach to tackle the Welded Beam Design Problem through
the application of the Water Evaporation Optimization Algorithm (WEOA), a nature-inspired …