Particle swarm optimization algorithm and its applications: a systematic review

AG Gad - Archives of computational methods in engineering, 2022 - Springer
Throughout the centuries, nature has been a source of inspiration, with much still to learn
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …

Advances in sine cosine algorithm: a comprehensive survey

L Abualigah, A Diabat - Artificial Intelligence Review, 2021 - Springer
Abstract The Sine Cosine Algorithm (SCA) is a population-based optimization algorithm
introduced by Mirjalili in 2016, motivated by the trigonometric sine and cosine functions …

Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate

J Zhou, Y Qiu, S Zhu, DJ Armaghani, C Li… - … Applications of Artificial …, 2021 - Elsevier
The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …

[HTML][HTML] Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

J Zhou, Y Qiu, DJ Armaghani, W Zhang, C Li, S Zhu… - Geoscience …, 2021 - Elsevier
A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …

An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models

H Chen, S Jiao, AA Heidari, M Wang, X Chen… - Energy Conversion and …, 2019 - Elsevier
Identifying the optimum parameters of photovoltaic models based on the measured current-
voltage info is a vital step in monitoring, simulating, and optimizing the photovoltaic systems …

A hybrid self-adaptive sine cosine algorithm with opposition based learning

S Gupta, K Deep - Expert Systems with Applications, 2019 - Elsevier
Real-world optimization problems demand an efficient meta-heuristic algorithm which
maintains the diversity of solutions and properly exploits the search space of the problem to …

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 …

Evolving kernel extreme learning machine for medical diagnosis via a disperse foraging sine cosine algorithm

J **a, D Yang, H Zhou, Y Chen, H Zhang, T Liu… - Computers in Biology …, 2022 - Elsevier
Kernel extreme learning machine (KELM) has been widely used in the fields of classification
and identification since it was proposed. As the parameters in the KELM model have a …

A novel chaotic Runge Kutta optimization algorithm for solving constrained engineering problems

BS Yıldız, P Mehta, N Panagant… - Journal of …, 2022 - academic.oup.com
This study proposes a novel hybrid metaheuristic optimization algorithm named chaotic
Runge Kutta optimization (CRUN). In this study, 10 diverse chaotic maps are being …

Designing of optimal digital IIR filter in the multi-objective framework using an evolutionary algorithm

S Chauhan, M Singh, AK Aggarwal - Engineering Applications of Artificial …, 2023 - Elsevier
In this work, an optimization technique ie diversity-driven multi-parent evolutionary algorithm
with adaptive non-uniform mutation (DDMPEA-ANUM) has been used to design a digital IIR …