A comprehensive survey of sine cosine algorithm: variants and applications
AB Gabis, Y Meraihi, S Mirjalili… - Artificial Intelligence …, 2021 - Springer
Abstract Sine Cosine Algorithm (SCA) is a recent meta-heuristic algorithm inspired by the
proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in …
proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in …
Solar photovoltaic power forecasting: a review
KJ Iheanetu - Sustainability, 2022 - mdpi.com
The recent global warming effect has brought into focus different solutions for combating
climate change. The generation of climate-friendly renewable energy alternatives has been …
climate change. The generation of climate-friendly renewable energy alternatives has been …
Slime mould algorithm: A new method for stochastic optimization
In this paper, a new stochastic optimizer, which is called slime mould algorithm (SMA), is
proposed based on the oscillation mode of slime mould in nature. The proposed SMA has …
proposed based on the oscillation mode of slime mould in nature. The proposed SMA has …
Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection
This research's genesis is in two aspects: first, a guaranteed solution for mitigating the grey
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …
An improved quantum-inspired differential evolution algorithm for deep belief network
W Deng, H Liu, J Xu, H Zhao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Deep belief network (DBN) is one of the most representative deep learning models.
However, it has a disadvantage that the network structure and parameters are basically …
However, it has a disadvantage that the network structure and parameters are basically …
Multi-population differential evolution-assisted Harris hawks optimization: Framework and case studies
The first powerful variant of the Harris hawks optimization (HHO) is proposed in this work.
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …
Boosted binary Harris hawks optimizer and feature selection
Y Zhang, R Liu, X Wang, H Chen, C Li - Engineering with Computers, 2021 - Springer
Feature selection is a required preprocess stage in most of the data mining tasks. This paper
presents an improved Harris hawks optimization (HHO) to find high-quality solutions for …
presents an improved Harris hawks optimization (HHO) to find high-quality solutions for …
Double adaptive weights for stabilization of moth flame optimizer: Balance analysis, engineering cases, and medical diagnosis
Moth flame optimization (MFO) is a swarm-based algorithm with mediocre performance and
marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode …
marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode …
Evolutionary biogeography-based whale optimization methods with communication structure: Towards measuring the balance
J Tu, H Chen, J Liu, AA Heidari, X Zhang… - Knowledge-Based …, 2021 - Elsevier
Abstract Whale Optimization Algorithm (WOA) is a popular swarm-based algorithm with
some spotted defects in its generated patterns during the searching phases. In this study, an …
some spotted defects in its generated patterns during the searching phases. In this study, an …
Ant colony optimization with horizontal and vertical crossover search: Fundamental visions for multi-threshold image segmentation
The ant colony optimization (ACO) is the most exceptionally fundamental swarm-based
solver for realizing discrete problems. In order to make it also suitable for solving continuous …
solver for realizing discrete problems. In order to make it also suitable for solving continuous …