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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“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…This is done by conducting the DOE on the two PSO optimizing parameters: the limit of change in particle velocity and the weight distribution factor. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy
Published 2023“…Air quality; Decision making; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Inference engines; Mapping; Mean square error; Multiobjective optimization; Optimal systems; Particle swarm optimization (PSO); Quality control; Renewable energy resources; Solar radiation; Uncertainty analysis; Adaptive neuro-fuzzy inference system; ANFIS; Multi objective algorithm; Multi objective particle swarm optimization; Multi-objective genetic algorithm; Renewable energies; Renewable energy generation; Solar radiation forecasting; Parameter estimation…”
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Optimal allocation and sizing of capacitor bank and distributed generation using particle swarm optimization
Published 2021“…The PSO algorithm allocates and determines the size of the capacitor and distributed generation in the power system. …”
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An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization
Published 2019“…Firstly, to detect the source, a Source Detection Algorithm (SDA) known as a Distributed Lévy Flight (DLF) is proposed. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. …”
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Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption
Published 2024“…To achieve this goal, we used the improved random walk algorithm to explore the distributed fire spots and a self-coordination mechanism based on the stigmergy as an indirect communication between the swarm drones, taking into account the collision avoidance factor, the amount of extinguishing fluid, and the flight range of the drones. …”
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…This is done by conducting the DOE on the two PSO optimizing parameters: the particle velocity limit and the weight distribution factor. …”
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Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique
Published 2013“…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems
Published 2019“…This research aimed to reduce total power losses and improve voltage profiles of the distribution system by proposing a practical swarm optimizion algorithm GA genetic algorithm to optimize DG size and location by taking into consideration increase number of DG units in the system. …”
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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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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid
Published 2023“…Thereafter, the Multi-Leader Particle Swarm Optimization algorithm (MLPSO), which is a novel evolutionary optimization technique in the field of power systems was developed and employed in the optimization process. …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Optimization of electrical wiring design in buildings using particle swarm optimization and genetic algorithm / Tuan Ahmad Fauzi Tuan Abdullah
Published 2017“…In this project, the main objective is to optimize the electrical distribution system design in buildings using optimization methods, which are Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Transformer T-joint optimization using particle swarm optimization and hemisphere-shape design of the core
Published 2017“…In this study, an intelligent algorithm was carried out using the particle swarm optimization technique (PSO) to propose the optimum design of T-joints for the core in three-phase distribution transformers. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems / Mohd Hafiz Mat Hussain
Published 2009“…In the developed simulator, users are able to set the parameters that have influences on particle swarm optimization performance. …”
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Impact of initialization of a modified particle swarm optimization on cooperative source searching
Published 2023“…Particle swarm optimization (PSO) is one of the famous algorithms have been used for source searching where its effectiveness depends on several factors. …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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