An improved arithmetic optimization algorithm and its application to determine the parameters of support vector machine

H Fang, X Fu, Z Zeng, K Zhong, S Liu - Mathematics, 2022 - mdpi.com
The arithmetic optimization algorithm (AOA) is a new metaheuristic algorithm inspired by
arithmetic operators (addition, subtraction, multiplication, and division) to solve arithmetic …

Hybrid grey wolf optimization algorithm–based support vector machine for groutability prediction of fractured rock mass

S Deng, X Wang, Y Zhu, F Lv, J Wang - Journal of Computing in …, 2019 - ascelibrary.org
Groutability determination is a very important task in grouting quality control. There is little
research on the groutability of cement-based grout in a fractured rock mass, and the …

A hybrid approach based on principal component analysis for power quality event classification using support vector machines

A Saxena, AM Alshamrani, AF Alrasheedi… - Mathematics, 2022 - mdpi.com
Power quality has emerged as a sincere denominator in the planning and operation of a
power system. Various events affect the quality of power at the distribution end of the system …

Soil salinity inversion based on novel spectral index

X Zhou, F Zhang, C Liu, H Kung… - Environmental Earth …, 2021 - Springer
Soil salinization is one of the most important causes for land degradation and desertification
and is an important threat to land management, farming activities, water quality, and …

[HTML][HTML] A study of bio-inspired computing in bioinformatics: a state-of-the-art literature survey

AK Mandal, PKD Sarma… - The Open …, 2023 - openbioinformaticsjournal.com
Background: Bioinspired computing algorithms are population-based probabilistic search
optimization approaches inspired by biological evolution and activity. These are highly …

Surface defect identification of Citrus based on KF-2D-Renyi and ABC-SVM

A Tan, G Zhou, M He - Multimedia Tools and Applications, 2021 - Springer
In allusion to the problems of citrus surface defect identification such as blurred edges,
unclear images, more interference and difficulty in defect identification, surface defect …

Swarm-Inspired Computing to Solve Binary Optimization Problems: A Backward Q-Learning Binarization Scheme Selector

M Becerra-Rozas, J Lemus-Romani… - Mathematics, 2022 - mdpi.com
In recent years, continuous metaheuristics have been a trend in solving binary-based
combinatorial problems due to their good results. However, to use this type of …

Chaotic binarization schemes for solving combinatorial optimization problems using continuous metaheuristics

F Cisternas-Caneo, B Crawford, R Soto, G Giachetti… - Mathematics, 2024 - mdpi.com
Chaotic maps are sources of randomness formed by a set of rules and chaotic variables.
They have been incorporated into metaheuristics because they improve the balance of …

Fraud detection model based on multi-verse features extraction approach for smart city applications

AS Sadiq, H Faris, AZ Ala'M, S Mirjalili… - Smart cities cybersecurity …, 2019 - Elsevier
The modern adoption of e-Commerce has accelerated the need for effective customer
protection, as part of the roadmap to expanding e-Commerce in smart cities. Before fully …

Grey wolf optimization algorithm based on dynamically adjusting inertial weight and levy flight strategy

Y Chen, J Xi, H Wang, X Liu - Evolutionary Intelligence, 2023 - Springer
Aiming at the problems of slow convergence speed, low convergence accuracy and easy to
fall into local optimum of grey wolf optimization algorithm (GWO), a dynamically adjusting …