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 …
A comprehensive survey on arithmetic optimization algorithm
Abstract Arithmetic Optimization Algorithm (AOA) is a recently developed population-based
nature-inspired optimization algorithm (NIOA). AOA is designed under the inspiration of the …
nature-inspired optimization algorithm (NIOA). AOA is designed under the inspiration of the …
HBO-LSTM: Optimized long short term memory with heap-based optimizer for wind power forecasting
The forecasting and estimation of wind power is a challenging problem in renewable energy
generation due to the high volatility of wind power resources, inevitable intermittency, and …
generation due to the high volatility of wind power resources, inevitable intermittency, and …
Improved arithmetic optimization algorithm and its application to carbon fiber reinforced polymer-steel bond strength estimation
X Shi, X Yu, M Esmaeili-Falak - Composite Structures, 2023 - Elsevier
In order to restore steel structures, bonding carbon fiber reinforced polymer (CFRP)
laminates have been widely used. The bond strength (PU) between the CFRP and steel …
laminates have been widely used. The bond strength (PU) between the CFRP and steel …
Performance investigation of state-of-the-art metaheuristic techniques for parameter extraction of solar cells/module
One of the greatest challenges for widespread utilization of solar energy is the low
conversion efficiency, motivating the needs of developing more innovative approaches to …
conversion efficiency, motivating the needs of developing more innovative approaches to …
Aquila optimizer based PSO swarm intelligence for IoT task scheduling application in cloud computing
This paper introduces IAO, a new swarm intelligence approach for addressing the challenge
of task scheduling in cloud computing. The proposed method uses conventional Aquila …
of task scheduling in cloud computing. The proposed method uses conventional Aquila …
Leveraging opposition-based learning for solar photovoltaic model parameter estimation with exponential distribution optimization algorithm
N Kullampalayam Murugaiyan, K Chandrasekaran… - Scientific Reports, 2024 - nature.com
Given the multi-model and nonlinear characteristics of photovoltaic (PV) models, parameter
extraction presents a challenging problem. This challenge is exacerbated by the propensity …
extraction presents a challenging problem. This challenge is exacerbated by the propensity …
Enhancing photovoltaic parameter estimation: integration of non-linear hunting and reinforcement learning strategies with golden jackal optimizer
The advancement of Photovoltaic (PV) systems hinges on the precise optimization of their
parameters. Among the numerous optimization techniques, the effectiveness of each often …
parameters. Among the numerous optimization techniques, the effectiveness of each often …
Approximating parameters of photovoltaic models using an amended reptile search algorithm
The appropriate selection of parameters of photovoltaic models is necessary for an accurate
evaluation, control, and optimization of photovoltaic systems. Even though various strategies …
evaluation, control, and optimization of photovoltaic systems. Even though various strategies …
Parameters identification of solar PV using hybrid chaotic northern goshawk and pattern search
This article proposes an effective evolutionary hybrid optimization method for identifying
unknown parameters in photovoltaic (PV) models based on the northern goshawk …
unknown parameters in photovoltaic (PV) models based on the northern goshawk …