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 …
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 …
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 …
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 …
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 …
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 …
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 …
combinatorial problems due to their good results. However, to use this type of …
Chaotic binarization schemes for solving combinatorial optimization problems using continuous metaheuristics
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 …
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
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 …
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 …
fall into local optimum of grey wolf optimization algorithm (GWO), a dynamically adjusting …