Results 21 to 30 of about 57,703 (300)
A statistical learning based approach for parameter fine-tuning of metaheuristics [PDF]
, 2016 Metaheuristics are approximation methods used to solve combinatorial optimization problems. Their performance usually depends on a set of parameters that need to be adjusted.
Calvet Liñán, Laura +3 more
core +2 more sources
The Solar System Algorithm: A Novel Metaheuristic Method for Global Optimization
IEEE Access, 2021 A novel metaheuristic algorithm for global optimization, called the Solar System Algorithm (SSA), is presented. The proposed algorithm imitates the orbiting behavior of some objects found in the solar system: i.e., Sun, planets, moons, stars, and black ...
Farouq Zitouni +2 more
doaj +1 more source
Metaheuristic Algorithms for Convolution Neural Network [PDF]
, 2016 A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry.
Arymurthy, Aniati Murni +2 more
core +3 more sources
Gold Rush Optimizer. A New Population-Based Metaheuristic Algorithm [PDF]
Operations Research and Decisions, 2023 Today's world is characterised by competitive environments, optimal resource utilization, and cost reduction, which has resulted in an increasing role for metaheuristic algorithms in solving complex modern problems. As a result, this paper introduces the
Kamran Zolfi
doaj
Mathematics, 2022 This paper proposes a new solution methodology based on a mixed-integer conic formulation to locate and size photovoltaic (PV) generation units in AC distribution networks with a radial structure.
Oscar Danilo Montoya +2 more
doaj +1 more source
Trigonometric words ranking model for spam message classification
IET Networks, EarlyView., 2022 Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi +7 more
wiley +1 more source
Firefly Algorithm, Stochastic Test Functions and Design Optimisation [PDF]
, 2010 Modern optimisation algorithms are often metaheuristic, and they are very promising in solving NP-hard optimization problems. In this paper, we show how to use the recently developed Firefly Algorithm to solve nonlinear design problems.
Yang, Xin-She
core +1 more source
IET Networks, EarlyView., 2023 We utilise a metaheuristic optimisation method, inspired by nature, called the Lévy‐flight firefly algorithm (LFA), to tackle the power regulation and user grouping in the NOMA systems. Abstract The non‐orthogonal multiple access strategies have shown promise to boost fifth generation and sixth generation wireless networks' spectral efficiency and ...
Zaid Albataineh +4 more
wiley +1 more source
Automatic Data Clustering Using Hybrid Firefly Particle Swarm Optimization Algorithm
IEEE Access, 2019 The firefly algorithm is a nature-inspired metaheuristic optimization algorithm that has become an important tool for solving most of the toughest optimization problems in almost all areas of global optimization and engineering practices.
Moyinoluwa B. Agbaje +2 more
doaj +1 more source
Buildings, 2022 This study proposes a generally applicable improvement strategy for metaheuristic algorithms, improving the algorithm’s accuracy and local convergence in finite element (FE) model updating.
Shiqiang Qin +3 more
doaj +1 more source