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ESO: An enhanced snake optimizer for real-world engineering problems
L Yao, P Yuan, CY Tsai, T Zhang, Y Lu… - Expert Systems with …, 2023 - Elsevier
Meta-heuristic algorithms are an essential way to solve realistic optimization problems.
Develo** effective, accurate, and stable meta-heuristic algorithms has become the goal of …
Develo** effective, accurate, and stable meta-heuristic algorithms has become the goal of …
[HTML][HTML] Improved bald eagle search algorithm for global optimization and feature selection
The use of metaheuristics is one of the most encouraging methodologies for taking care of
real-life problems. Bald eagle search (BES) algorithm is the latest swarm-intelligence …
real-life problems. Bald eagle search (BES) algorithm is the latest swarm-intelligence …
Blood-sucking leech optimizer
In this paper, a new meta-heuristic optimization algorithm motivated by the foraging
behaviour of blood-sucking leeches in rice fields is presented, named Blood-Sucking Leech …
behaviour of blood-sucking leeches in rice fields is presented, named Blood-Sucking Leech …
[HTML][HTML] Stochastic optimal power flow analysis of power systems with wind/PV/TCSC using a developed Runge Kutta optimizer
Recently, renewable energy resources such as wind turbines (WTs) and photovoltaic (PV)
systems are wildly installed in electrical systems. However, the main challenge that related …
systems are wildly installed in electrical systems. However, the main challenge that related …
[HTML][HTML] A quasi-oppositional learning of updating quantum state and Q-learning based on the dung beetle algorithm for global optimization
Z Wang, L Huang, S Yang, D Li, D He… - Alexandria Engineering …, 2023 - Elsevier
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 …
Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization
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 …
its proficiency. However, due to its reliance on the alpha wolf for guiding the position …
[HTML][HTML] Stochastic optimal power flow analysis of power system with renewable energy sources using Adaptive Lightning Attachment Procedure Optimizer
The integration of several renewable energy sources (RESs), such as photovoltaic
generation (PVG) and wind turbine generation (WTG), introduces a significant amount of …
generation (PVG) and wind turbine generation (WTG), introduces a significant amount of …
A local opposition-learning golden-sine grey wolf optimization algorithm for feature selection in data classification
Z Li - Applied Soft Computing, 2023 - Elsevier
The classification problem is an important research topic in machine learning and data
mining. Feature selection can remove irrelevant and redundant features and improve …
mining. Feature selection can remove irrelevant and redundant features and improve …
Combined cubic generalized ball surfaces: Construction and shape optimization using an enhanced JS algorithm
G Hu, M Li, J Zhong - Advances in Engineering Software, 2023 - Elsevier
The construction and shape optimization of complex shape-adjustable surfaces is a crucial
and intractable technique in Computer Aided geometric Design (CAGD), which has a wide …
and intractable technique in Computer Aided geometric Design (CAGD), which has a wide …
Enhanced marine predator algorithm for global optimization and engineering design problems
SB Aydemir - Advances in Engineering Software, 2023 - Elsevier
Marine predator algorithm adopts the policy of optimal encounter rate in biological
interaction between predator and prey, inspired by the Lévy and Brownian motions …
interaction between predator and prey, inspired by the Lévy and Brownian motions …