Search Results - (( weight distribution swarm algorithm ) OR ( parameters estimation case algorithm ))
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An improved particle swarm optimization algorithm for data classification
Published 2023“…In this study, we propose an improved PSO algorithm variant that enhances convergence speed and population diversity by applying pseudo-random sequences and opposite rank inertia weights instead of using random distributions for initialisation. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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Optimal multiple distributed generation output through rank evolutionary particle swarm optimization
Published 2015“…Moreover, the local best (P-best) and global best (G(best)) values are obtained in simplify manner in the REPSO algorithm. The performance of this new algorithm will be compared to 3 well-known PSO methods, which are Conventional Particle Swarm Optimization (CPSO), Inertia Weight Particle Swarm Optimization (IWPSO), and Iteration Particle Swarm Optimization (IPSO) on 10 mathematical benchmark functions, and solving the optimal DG output problem. …”
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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An adaptive localization system using particle swarm optimization in a circular distribution form
Published 2016“…The proposed algorithm uses PSO to generate several particles that have circular distribution around one access point (AP). …”
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Flash flood evacuation with discrete particle swarm optimization / Marina Yusoff
Published 2011“…Currently, no proper procedure is available in managing the evacuation vehicle assignment problem (EVAP) and evacuation vehicle routing problem (EVRP). A discrete particle swarm optimization (DPSO) algorithm is proposed to solve the EVRP and the EVRP. …”
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Thesis -
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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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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…In this work, a real-world MO problem (resin-bonded sand mould system) is tackled using Particle Swarm Optimization (PSO) in conjunction with the weighted-sum approach. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…In this work, a real-world MO problem (resin-bonded sand mould system) is tackled using Particle Swarm Optimization (PSO) in conjunction with the weighted-sum approach. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…In this work, a real-world MO problem (resin-bonded sand mould system) is tackled using Particle Swarm Optimization (PSO) in conjunction with the weighted-sum approach. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…In this work, a real-world MO problem (resin-bonded sand mould system) is tackled using Particle Swarm Optimization (PSO) in conjunction with the weighted-sum approach. …”
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A Particle Swarm Optimization Trained Feedforward Neural Network for Under-Voltage Load Shedding
Published 2023“…Hence, this article introduces an optimal UVLS method using a feedforward artificial neural network (ANN) model trained with the particle swarm optimization (PSO) algorithm to obtain the optimal load shedding amount for a distribution system. …”
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A Particle Swarm Optimization Trained Feedforward Neural Network for Under-Voltage Load Shedding
Published 2023“…Hence, this article introduces an optimal UVLS method using a feedforward artificial neural network (ANN) model trained with the particle swarm optimization (PSO) algorithm to obtain the optimal load shedding amount for a distribution system. …”
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A Particle Swarm Optimization Trained Feedforward Neural Network for Under-Voltage Load Shedding
Published 2023“…Hence, this article introduces an optimal UVLS method using a feedforward artificial neural network (ANN) model trained with the particle swarm optimization (PSO) algorithm to obtain the optimal load shedding amount for a distribution system. …”
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A Particle Swarm Optimization Trained Feedforward Neural Network for Under-Voltage Load Shedding
Published 2023“…Hence, this article introduces an optimal UVLS method using a feedforward artificial neural network (ANN) model trained with the particle swarm optimization (PSO) algorithm to obtain the optimal load shedding amount for a distribution system. …”
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Flash flood evacuation with discrete particle swarm optimization / Marina Yusoff
Published 2012“…Currently, no proper procedure is available in managing the evacuation vehicle assignmentproblem (EVAP) and evacuation vehicle routing problem (EVRP). A discrete particle swarm optimization (DPSO) algorithm is proposed to solve the EVRP and the EVRP. …”
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Book Section -
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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
Published 2023“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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Parameter estimation of cocomo model using the jaya algorithm for software cost estimation
Published 2019“…The Constructive Cost Model (COCOMO) is a procedural software cost estimation model developed by Barry W. Boehm. In this case, the estimation of value of the COCOMO model parameters are determined for the cost and time estimation of the COCOMO model. …”
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