Improved sine cosine algorithm with crossover scheme for global optimization
Abstract Sine Cosine Algorithm is a recently developed algorithm based on the
characteristics of sine and cosine trigonometric functions, to solve global optimization …
characteristics of sine and cosine trigonometric functions, to solve global optimization …
Chaotic oppositional sine–cosine method for solving global optimization problems
This study proposed an improved sine–cosine algorithm (SCA) for global optimization tasks.
The SCA is a meta-heuristic method ground on sine and cosine functions. It has found its …
The SCA is a meta-heuristic method ground on sine and cosine functions. It has found its …
Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec
Abstract World Health Organization (WHO) stated COVID-19 as a pandemic in March 2020.
Since then, 26,795,847 cases have been reported worldwide, and 878,963 lost their lives …
Since then, 26,795,847 cases have been reported worldwide, and 878,963 lost their lives …
Sine cosine grey wolf optimizer to solve engineering design problems
Balancing the exploration and exploitation in any nature-inspired optimization algorithm is
an essential task, while solving the real-world global optimization problems. Therefore, the …
an essential task, while solving the real-world global optimization problems. Therefore, the …
A reinforcement learning-based hybrid Aquila Optimizer and improved Arithmetic Optimization Algorithm for global optimization
H Liu, X Zhang, H Zhang, C Li, Z Chen - Expert Systems with Applications, 2023 - Elsevier
This study constructs a reinforcement learning-based hybrid algorithm for Aquila Optimizer
(AO) and improved Arithmetic Optimization Algorithm (IAOA). The point of the hybrid …
(AO) and improved Arithmetic Optimization Algorithm (IAOA). The point of the hybrid …
A new fusion of salp swarm with sine cosine for optimization of non-linear functions
The foremost objective of this article is to develop a novel hybrid powerful meta-heuristic that
integrates the salp swarm algorithm with sine cosine algorithm (called HSSASCA) for …
integrates the salp swarm algorithm with sine cosine algorithm (called HSSASCA) for …
Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization
This paper introduces a new variant of the metaheuristic algorithm based on the naked mole
rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for …
rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for …
Multiple black hole inspired meta-heuristic searching optimization for combinatorial testing
HNN Al-Sammarraie, DNA Jawawi - Ieee Access, 2020 - ieeexplore.ieee.org
Combinatorial searching-based software testing (CSST) is a challenging optimization
procedure. The achievement of optimal solutions involves a careful formulation of the …
procedure. The achievement of optimal solutions involves a careful formulation of the …
Predicting cervical hyperextension injury: a covariance guided sine cosine support vector machine
G Liu, W Jia, M Wang, AA Heidari, H Chen, Y Luo… - IEEE …, 2020 - ieeexplore.ieee.org
This study proposes an effective intelligent predictive model for prediction of cervical
hyperextension injury. The prediction model is constructed by combing an improved sine …
hyperextension injury. The prediction model is constructed by combing an improved sine …
Q-learning embedded sine cosine algorithm (QLESCA)
Abstract Sine Cosine Algorithm (SCA) was recognized as a lightweight, efficient, and has a
clear math principal optimizer. However, SCA still suffers from a set of problems such as …
clear math principal optimizer. However, SCA still suffers from a set of problems such as …