Neural decoding of EEG signals with machine learning: a systematic review
Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …
Crow search algorithm: theory, recent advances, and applications
In this article, a comprehensive overview of the Crow Search Algorithm (CSA) is introduced
with detailed discussions, which is intended to keep researchers interested in swarm …
with detailed discussions, which is intended to keep researchers interested in swarm …
Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy
Although the continuous version of ant colony optimizer (ACOR) has been successfully
applied to various problems, there is room to boost its stability and improve convergence …
applied to various problems, there is room to boost its stability and improve convergence …
Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis
Y Zhang, R Liu, AA Heidari, X Wang, Y Chen, M Wang… - Neurocomputing, 2021 - Elsevier
Bankruptcy prediction is a crucial application in financial fields to aid in accurate decision
making for business enterprises. Many models may stagnate to low-accuracy results due to …
making for business enterprises. Many models may stagnate to low-accuracy results due to …
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 …
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 …
Dimension decided Harris hawks optimization with Gaussian mutation: Balance analysis and diversity patterns
Harris hawks optimization (HHO) is a newly developed swarm-based algorithm and the most
popular optimizer in the recent year, which mimics the cooperation behavior of Harris hawks …
popular optimizer in the recent year, which mimics the cooperation behavior of Harris hawks …
Flood susceptibility assessment using novel ensemble of hyperpipes and support vector regression algorithms
Recurrent floods are one of the major global threats among people, particularly in
developing countries like India, as this nation has a tropical monsoon type of climate …
developing countries like India, as this nation has a tropical monsoon type of climate …
Application of support vector machines for accurate prediction of convection heat transfer coefficient of nanofluids through circular pipes
M Safdari Shadloo - International Journal of Numerical Methods for …, 2021 - emerald.com
Purpose Convection is one of the main heat transfer mechanisms in both high to low
temperature media. The accurate convection heat transfer coefficient (HTC) value is …
temperature media. The accurate convection heat transfer coefficient (HTC) value is …
Random learning gradient based optimization for efficient design of photovoltaic models
W Zhou, P Wang, AA Heidari, X Zhao… - Energy Conversion and …, 2021 - Elsevier
How to effectively realize the parameter identification of different photovoltaic models has
gradually become a research hotspot. This paper proposes an improved gradient-based …
gradually become a research hotspot. This paper proposes an improved gradient-based …