[HTML][HTML] Recent advances in harris hawks optimization: A comparative study and applications
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
[HTML][HTML] Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review
Multilevel Thresholding (MLT) is considered as a significant and imperative research field in
image segmentation that can efficiently resolve difficulties aroused while analyzing the …
image segmentation that can efficiently resolve difficulties aroused while analyzing the …
[HTML][HTML] A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations
The supply-demand-based optimization (SDO) is among the recent stochastic approaches
that have proven its capability in solving challenging engineering tasks. Owing to the non …
that have proven its capability in solving challenging engineering tasks. Owing to the non …
Adaptive Harris hawks optimization with persistent trigonometric differences for photovoltaic model parameter extraction
In this paper, an adaptive Harris hawk optimization with persistent trigonometric (sine–
cosine)-differences (ADHHO) is proposed for parameter identification of Photovoltaic (PV) …
cosine)-differences (ADHHO) is proposed for parameter identification of Photovoltaic (PV) …
DTCSMO: An efficient hybrid starling murmuration optimizer for engineering applications
Starling murmuration optimizer is a newly well-developed swarm intelligence algorithm
inspired by the behavior of starlings during stunning murmuration and has performed …
inspired by the behavior of starlings during stunning murmuration and has performed …
[HTML][HTML] Chaotic harris hawks optimization with quasi-reflection-based learning: An application to enhance cnn design
The research presented in this manuscript proposes a novel Harris Hawks optimization
algorithm with practical application for evolving convolutional neural network architecture to …
algorithm with practical application for evolving convolutional neural network architecture to …
Leader Harris Hawks algorithm based optimal controller for automatic generation control in PV-hydro-wind integrated power network
The work in this manuscript aims at designing a novel control strategy based on the Model
Predictive Controller aided with Leader Harris Hawks Optimization (MPC-LHHO) algorithm …
Predictive Controller aided with Leader Harris Hawks Optimization (MPC-LHHO) algorithm …
[HTML][HTML] An improved weighted mean of vectors algorithm for microgrid energy management considering demand response
The integration of demand response programs (DRPs) into the energy management (EM)
system of microgrids (MGs) helps in improving the load characteristics by allowing …
system of microgrids (MGs) helps in improving the load characteristics by allowing …
[HTML][HTML] Utilizing controlled plug-in electric vehicles to improve hybrid power grid frequency regulation considering high renewable energy penetration
This study proposes an incorporated strategy based on energy storage systems (ESSs) like
plug-in electric vehicles (PEVs) with load frequency control (LFC) to enhance the frequency …
plug-in electric vehicles (PEVs) with load frequency control (LFC) to enhance the frequency …
Parameter estimation of ECM model for Li-Ion battery using the weighted mean of vectors algorithm
W Merrouche, B Lekouaghet, E Bouguenna… - Journal of Energy …, 2024 - Elsevier
Accurate parameter estimation of the equivalent circuit model (ECM) for Li-Ion batteries
(LiBs) allows for better behavior modeling and understanding. This is crucial for various …
(LiBs) allows for better behavior modeling and understanding. This is crucial for various …