Search Results - (( swarm optimization method algorithm ) OR ( data distribution using algorithm ))
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An improved particle swarm optimization algorithm for data classification
Published 2023“…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…This method was proposed to increase the exploration and the exploitation of the Segment Particle Swarm Optimization algorithm (Se-PSO). …”
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Two objectives big data task scheduling using swarm intelligence in cloud computing
Published 2016“…Then, it proposes a type of swarm intelligence called Particle Swarm Optimization (PSO) algorithm to diminish cost though meeting deadlines. …”
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Optimal Power Flow of power systems using Harris Hawks Optimization and Salp Swarm Algorithm
Published 2021“…The obtained results showed the decent improvement comparing to other swarm-based techniques like Whale Optimization Algorithm (WOA), Math Flame (MF), and Glowworm Optimization Algorithm (GOA) in terms of convergence performance and quality. …”
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Optimal configuration of wind farms in radial distribution system using particle swarm optimization technique
Published 2018“…The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. …”
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Optimal configuration of wind farms in radial distribution system using particle swarm optimization technique
Published 2018“…The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. …”
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Power-efficient wireless coverage using minimum number of uavs
Published 2023“…Antennas; Disasters; Genetic algorithms; Iterative methods; K-means clustering; Particle swarm optimization (PSO); 3-D placements; Artificial bee colony; Efficient 3d placement; Genetic algorithm; K-means; Particle swarm optimization; Placement algorithm; Power efficient; Unmanned aerial vehicle; Wireless coverage; Unmanned aerial vehicles (UAV); algorithm; animal; bee; Algorithms; Animals; Bees; Unmanned Aerial Devices…”
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A review on the applications of PSO-based algorithm in demand side management: Challenges and opportunities
Published 2023“…Owing to its simplicity and consistent performance in fast convergence time, Particle Swarm Optimization (PSO) is widely used as a part of the swarm AI algorithm and has become a prominent technique in the optimization process to exploit the full benefit of the demand-side program. …”
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Modeling Of Electrical Distribution Networks With Particle Swarm Optimization Technique For The Improvement Of Voltage Profile And Loss Reduction
Published 2016“…The data of series impedance is also used to investigate power flow in all segments in the distribution system. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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Enhancing high-dimensional streaming data analysis: optimizing Online Feature Selection for handling drift using optimization technique and ensemble learning
Published 2024“…The PSO-OSFS method is underpinned by the adaptive threshold particle representation of particle swarm optimization and enhanced fitness function using minimization of mean absolute deviation of dependency among fea-ture subsets. …”
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A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization
Published 2022“…The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…Given the NP-Hard nature of the three models proposed in this thesis, two metaheuristic algorithms have been developed. A hybrid Particle Swarm Optimization-Bacterial Foraging Algorithm is developed for solving the single objective LIRP model. …”
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Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems
Published 2017“…The three objective functions, i.e., power loss reduction, voltage stability improvement, and voltage deviation minimization are optimized using advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization method. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The proposed framework and methods are evaluated using the state-of-the-art datasets from the NASA metric data repository. …”
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Controller placement problem in the optimization of 5G based SDN and NFV architecture
Published 2021“…If the control plane fails to improve system resilience quality, A reliable RAMCP is formulated as an optimal solution for fault tolerance. Furthermore, the approach is extended with a Particle Swarm Algorithm (PSO) and presented as a hybrid RASCP to validate the optimal location and number of controllers. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…Therefore, this automatic database is designed to provide an alternative for robust neural network forecasting using statistical robust estimators of M-estimators, Iterated Least Median Square (ILMedS) and Particle Swarm Optimization on Least Median Square (PSO-LMedS), replacing the MSE cost function to handle time series data with missing values, outliers and noise, which always exist in real-life-time series data. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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