Walrus optimizer: A novel nature-inspired metaheuristic algorithm
M Han, Z Du, KF Yuen, H Zhu, Y Li, Q Yuan - Expert Systems with …, 2024 - Elsevier
Metaheuristic algorithms are intelligent optimization approaches that lead the searching
procedure through utilizing exploitation and exploration. The increasing complexity of real …
procedure through utilizing exploitation and exploration. The increasing complexity of real …
[HTML][HTML] Hierarchical RIME algorithm with multiple search preferences for extreme learning machine training
This paper introduces a hierarchical RIME algorithm with multiple search preferences
(HRIME-MSP) to tackle complex optimization problems. Although the original RIME …
(HRIME-MSP) to tackle complex optimization problems. Although the original RIME …
Efficient state of charge estimation of lithium-ion batteries in electric vehicles using evolutionary intelligence-assisted GLA–CNN–Bi-LSTM deep learning model
The battery's performance heavily influences the safety, dependability, and operational
efficiency of electric vehicles (EVs). This paper introduces an innovative hybrid deep …
efficiency of electric vehicles (EVs). This paper introduces an innovative hybrid deep …
Multi-objective group learning algorithm with a multi-objective real-world engineering problem
The concern of multi-objective optimization is to deal with optimization problems with more
than one objective that should be optimized at the same time. In this paper, a new multi …
than one objective that should be optimized at the same time. In this paper, a new multi …
CDDO–HS: child drawing development optimization–harmony search algorithm
Child drawing development optimization (CDDO) is a recent example of a metaheuristic
algorithm. The motive for inventing this method is children's learning behavior and cognitive …
algorithm. The motive for inventing this method is children's learning behavior and cognitive …
Balancing individual and collective strategies: A new approach in metaheuristic optimization
Metaheuristic approaches commonly disregard the individual strategies of each agent within
a population, focusing primarily on the collective best solution discovered so far. While this …
a population, focusing primarily on the collective best solution discovered so far. While this …
[HTML][HTML] Computational and intelligence modeling analysis of pharmaceutical freeze drying for prediction of temperature in the process
Accurate temperature prediction is crucial for various scientific and engineering applications,
yet it remains challenging due to the complex relationships between spatial coordinates and …
yet it remains challenging due to the complex relationships between spatial coordinates and …
A boosted African vultures optimization algorithm combined with logarithmic weight inspired novel dynamic chaotic opposite learning strategy
Abstract The African Vultures Optimization Algorithm (AVOA), a newly developed swarm-
intelligence meta-heuristics motivated by the scavenging and hunting behaviors of African …
intelligence meta-heuristics motivated by the scavenging and hunting behaviors of African …
ASCAEO: accelerated sine cosine algorithm hybridized with equilibrium optimizer with application in image segmentation using multilevel thresholding
S Thapliyal, N Kumar - Evolving Systems, 2024 - Springer
The current trend in global optimization research is to hybridize multiple variants to improve
the quality of solutions to real-world problems that have recently arisen in practise. This …
the quality of solutions to real-world problems that have recently arisen in practise. This …
Hyperbolic Sine Optimizer: a new metaheuristic algorithm for high performance computing to address computationally intensive tasks
S Thapliyal, N Kumar - Cluster Computing, 2024 - Springer
In recent decades, the demand for optimization techniques has grown due to rising
complexity in real-world problems. Hence, this work introduces the Hyperbolic Sine …
complexity in real-world problems. Hence, this work introduces the Hyperbolic Sine …