Advances in teaching-learning-based optimization algorithm: A comprehensive survey
Teaching-learning-based optimization (TLBO) algorithm which imitates the teaching-
learning process in a classroom, is one of population-based heuristic stochastic swarm …
learning process in a classroom, is one of population-based heuristic stochastic swarm …
A sinh cosh optimizer
Currently, meta-heuristic algorithms have been widely studied and applied, but balancing
exploration and exploitation remains a challenge. In this study, a novel meta-heuristic …
exploration and exploitation remains a challenge. In this study, a novel meta-heuristic …
Simulated annealing-based dynamic step shuffled frog lea** algorithm: Optimal performance design and feature selection
The shuffled frog lea** algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …
combinatorial optimization problem, which effectively combines the memetic algorithm …
An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems
The sine cosine algorithm (SCA) is a well-known meta-heuristic optimization algorithm. SCA
has received much attention in various optimization fields due to its simple structure and …
has received much attention in various optimization fields due to its simple structure and …
Multi-threshold image segmentation using a multi-strategy shuffled frog lea** algorithm
Medical image segmentation, which is a complex and fundamental step in medical image
processing, can help doctors make more precise decisions on patient diagnosis. Although …
processing, can help doctors make more precise decisions on patient diagnosis. Although …
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) …
An optimized machine learning framework for predicting intradialytic hypotension using indexes of chronic kidney disease-mineral and bone disorders
Intradialytic hypotension (IDH) is the most common acute complication in hemodialysis (HD)
sessions and is associated with increased morbidity and mortality in HD patients. To prevent …
sessions and is associated with increased morbidity and mortality in HD patients. To prevent …
Multi-level thresholding segmentation for pathological images: Optimal performance design of a new modified differential evolution
The effective analytical processing of pathological images is crucial in promoting the
development of medical diagnostics. Based on this matter, in this research, a multi-level …
development of medical diagnostics. Based on this matter, in this research, a multi-level …
A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system
Accurate estimations of battery state-of-charge (SOC) for energy storage systems are
popular research topics in recent years. Numerous challenges remain in several aspects …
popular research topics in recent years. Numerous challenges remain in several aspects …
A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting
Solar power is an important renewable energy resource and acts as a major contributor to
replacing fossil fuel generators and reducing carbon emissions. However, the intermittent …
replacing fossil fuel generators and reducing carbon emissions. However, the intermittent …