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Showing 1 to 20 of 159 for “"Particle Swarm Optimization"”.
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Dual Satellite Coverage using Particle Swarm Optimization
… analysis of the optimal solutions generated by a Particle Swarm Optimization method is completed using a cost function with different weights for the time, fuel, and angle terms. Three different scenarios are presented: a single burn case, a double burn case, and a four burn case. The results are …
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Experimental analysis on the operation of Particle Swarm Optimization
In Particle Swarm Optimization, it has been observed that swarms often stall as opposed to converge. A stall occurs when all of the forward progress that could occur is instead rejected as Failed Exploration. Since the swarms particles are in good regions of the search space with the potential to …
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Particle swarm optimization applications to mpeg-4 transmission over ZigBee
… needs to be optimized at the targeted bitrate. Optimization techniques are widely used in engineering and computer science as well as being used in real environment applications to overcome complex issues and in particular; an artificial intelligence technique known as Particle Swann …
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Application of particle swarm optimization in adaptive self-interference cancellation
This thesis investigates the application of particle swarm optimization in self-interference cancellation. To achieve cancellation, the receiver has to differentiate between the transmit and receive signal. The transmit signal is already known at the transmitting side but it undergoes some …
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An improved data classification framework based on fractional particle swarm optimization
Particle Swarm Optimization (PSO) is a population based stochastic optimization technique which consist of particles that move collectively in iterations to search for the most optimum solutions. However, conventional PSO is prone to lack of convergence and even stagnation in complex high …
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Dynamic electronic asset allocation comparing genetic algorithm with particle swarm optimization
… 2) Comparing performance of Genetic Algorithm to Particle Swarm Optimization (PSO) algorithm. This research problem implemented Genetic Algorithm in C++ and used QT Data Visualization for displaying three-dimensional space, pheromone, and Terrain. The Genetic algorithm implementation maintained …
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Optimization-based mechanism synthesis using multi-objective parallel asynchronous particle swarm optimization
A distributed variant of multi-objective particle swarm optimization (MOPSO) called multi-objective parallel asynchronous particle swarm optimization (MOPAPSO) is presented, and the effects of distribution of objective function calculations to slave processors on the results and performance are …
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Identifying near-earth asteroid targets for human exploration using particle swarm optimization
… to help identify these targets is the particle swarm optimization (PSO) technique, a metaheuristic swarming algorithm. The optimizer that was developed minimizes the total mission delta-V, given a particular epoch date, whilst optimizing four time parameters, namely, the ideal time to …
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Stochastic Approximation Algorithms With Applications To Particle Swarm Optimization, Adaptive Optimization, And Consensus
… 2, we use stochastic approximation to analyze Particle Swarm Optimization (PSO) algorithm. We introduce four coefficients and rewrite the PSO procedure as a stochastic approximation type iterative algorithm. Then we analyze its convergence using weak convergence method. It is proved that a …
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Design Validation of RTL Circuits using Binary Particle Swarm Optimization and Symbolic Execution
Over the last two decades, chip design has been conducted at the register transfer (RT) Level using Hardware Descriptive Languages (HDL), such as VHDL and Verilog. The modeling at the behavioral level not only allows for better representation and understanding of the design, but also allows for …
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Efficient Merging and Decomposition Variants of Cooperative Particle Swarm Optimization for Large Scale Problems
For large-scale optimization problems (LSOPs), an increased problem size reduces performance by both increasing the landscape complexity, as well as exponentially increasing the search space size. These contributing factors make up the "curse of dimensionality", which is addressed either by …
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Particle swarm optimization for dynamically changing environments with particular focus on scalability and switching cost
… and adaptation is central to their resilience. Optimization problems are no exception to this maxim. Indeed, viability of businesses depends heavily on their effectiveness in responding to a change in the myriad of optimization problems they entail. Changes in optimization problems usually are …
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Harmonic reduction of a single-phase multilevel inverter using genetic algorithm and particle swarm optimization
… are focusing on multilevel inverter topic in optimization on voltage output, reduce total harmonics distortion, modulation technique and switching configuration. Standalone application multilevel inverter is high focused due to the rise of renewable energy policy all around the world. Hence, …
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Initial Orbit Determination of Uncooperative Satellites Using Particle Swarm Optimization From the Point of View of a Novel Observer Orbit
… from the point of view of novel orbits using particle swarm optimization (PSO) algorithm is explored. Two cost functions for the PSO algorithm are investigated. The first cost function investigated uses the solution to Lambert’s Problem to estimate the initial velocity of the target. The …
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
… the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. Yet, the previous research did not take into account obstacles’ existence in the field and …
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Optimal distribution of the relaxation behavior of linear viscoelastic materials by the particle swarm optimization method applied to the problem of a twisting shaft
… framework for the material distribution optimization problem of a linear viscoelastic material. The distribution of the relaxation behavior (coefficients of the Prony series expansion) across the system was obtained to achieve a target performance of the dynamic system by the particle …
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Permeability Distribution Estimation Based on Semi-Analytical Reservoir Simulator
… For our semi-analytical simulator, the choice of optimization algorithms to minimize the objective function becomes of vital importance. For our simulator, we considered both gradient based methods and non-gradient based methods. Gradient based algorithms have the big advantage of much faster …
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New numerical methods for open-loop and feedback solutions to dynamic optimization problems
… of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each …
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Improved cuckoo search based neural network learning algorithms for data classification
… an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and …
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