A powerful meta-heuristic search algorithm for solving global optimization and real-world solar photovoltaic parameter estimation problems
The teaching-learning-based artificial bee colony (TLABC) is a new hybrid swarm-based
metaheuristic search algorithm. It combines the exploitation of the teaching learning-based …
metaheuristic search algorithm. It combines the exploitation of the teaching learning-based …
An improved reptile search algorithm with ghost opposition-based learning for global optimization problems
In 2021, a meta-heuristic algorithm, Reptile Search Algorithm (RSA), was proposed. RSA
mainly simulates the cooperative predatory behavior of crocodiles. Although RSA has a fast …
mainly simulates the cooperative predatory behavior of crocodiles. Although RSA has a fast …
Stochastic paint optimizer: theory and application in civil engineering
This paper presents an art-inspired optimization algorithm, which is called Stochastic Paint
Optimizer (SPO). The SPO is a population-based optimizer inspired by the art of painting …
Optimizer (SPO). The SPO is a population-based optimizer inspired by the art of painting …
Development of the Natural Survivor Method (NSM) for designing an updating mechanism in metaheuristic search algorithms
Meta-heuristic search algorithms (MHSs) are methods that take their inspiration from nature.
However, the fitness value information used in the design of the update mechanism in MHSs …
However, the fitness value information used in the design of the update mechanism in MHSs …
Fitness–Distance Balance based adaptive guided differential evolution algorithm for security-constrained optimal power flow problem incorporating renewable energy …
One of the most difficult types of problems computationally is the security-constrained
optimal power flow (SCOPF), a non-convex, nonlinear, large-scale, nondeterministic …
optimal power flow (SCOPF), a non-convex, nonlinear, large-scale, nondeterministic …
Optimal solution of the combined heat and power economic dispatch problem by adaptive fitness-distance balance based artificial rabbits optimization algorithm
Combined heat and power economic dispatch (CHPED) problem is one of the most widely
handled, optimization problem by researchers in modern power systems. CHPED problem is …
handled, optimization problem by researchers in modern power systems. CHPED problem is …
Meta-heuristic search algorithms in truss optimization: Research on stability and complexity analyses
HT Öztürk, HT Kahraman - Applied Soft Computing, 2023 - Elsevier
Although they are among the most researched real world engineering design problems, it is
encountered with significant problems in the optimization of structural truss bar problems …
encountered with significant problems in the optimization of structural truss bar problems …
Economical operation of modern power grids incorporating uncertainties of renewable energy sources and load demand using the adaptive fitness-distance balance …
With the increase in the world population and the rapid developments in technology, the
energy demands on modern electricity grids are also rising. In order to meet these demands …
energy demands on modern electricity grids are also rising. In order to meet these demands …
[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 …
Evolutionary gate recurrent unit coupling convolutional neural network and improved manta ray foraging optimization algorithm for performance degradation …
Z Tao, C Zhang, J Xiong, H Hu, J Ji, T Peng, MS Nazir - Applied Energy, 2023 - Elsevier
Performance degradation prediction is an effective method to improve the durability of
proton exchange membrane fuel cell (PEMFC). In this study, a hybrid deep learning model …
proton exchange membrane fuel cell (PEMFC). In this study, a hybrid deep learning model …