[PDF] Top 20 3.6.2 Particle Swarm Optimization - PSOGeneral

... Continuous Optimization Problems ACO algorithms have been extended to deal with continuous optimization ...continuous optimization in ...continuous optimization were reported in many works ... See full document

... of optimization obtained by PSO algorithm were slightly better than tabu-search approach (Kolahan & Liang, 2000) since for both cases showing an improvement about ... See full document

... systems. Swarm intelligence is one of the scientific fields that are based on natural swarms, such as ant colonies, bee colonies, group behavior of bacterium, rivers (group of water drops) ...colony ... See full document

... numerical optimization, which apply mathematical or statistical techniques to minimize, or maximize, an objective function defined over a parameter ...Colony Optimization (ACO) [4] and Particle ... See full document

... novel optimization algorithm SODOCK is used for solving protein–ligand docking ...on particle swarm optimization and a local search ... See full document

... global optimization methods have been proposed to solve this problem such as: simulated annealing [2]; neural networks [7]; particle swarm optimization and genetic algorithm ... See full document

... In microwave applications, a neural network can train to mimic the electrical behavior of the circuit. Then, it can be used in high-level simulation and design, providing a fast response to the learned task [3], ... See full document

... REAL-time object tracking is the critical task in many computer vision applications such as surveillance. Two major components can be distinguished in a typical visual tracker. Target Representation and Localization is ... See full document

... the optimization of multidimensional ...of 2 π / N which cannot be sure the value of the cut-off ...and Particle Swarm Optimization(PSO) algorithm[6], although those methods do ... See full document

... A GRASP approach for the MCP is presented in [1], while in [3] and [4] Genetic Algorithms are ap- plied for the problem. The GRASP metaheuristic proposed by Feo and Resende [2] has been successfully tested ... See full document

... in the literature [3-6]. Array pattern synthesis techniques for designing of broadband FIR beam former with constant main lobe response and minimum side lobe level (SLL) have been discussed in [3-5]. ... See full document

... several optimization approaches for such ...[6–8], particle swarm optimization (PSO) [9, 10], ant colony optimization (ACO) [11–13], differential evolution (DE) [14], clonal ... See full document

... Phased array antennas are widely used in Radar systems because of their rapid and accurate beam scanning capabilities [1]. For practical Radar applications, it is required that the phased array produces low s idelobe ... See full document

... Particle Swarm Optimization, PSO, is a stochastic optimization technique which was developed by Kennedy and Eberhart in 1995, inspired by the behavior of bird flocks, or bee swarms ...based ... See full document

... the optimization of the transmitted power to minimize the interference between the users and maximize the energy efficiency, considering the quality of service (QoS) restrictions in terms of signal-to-noise-plus ... See full document

... To change the speed from the low rotating rotor to the high rotating generator a gearbox is used [5]. In their transmissions robotic systems that need to present high torques at the end effectors typically contain high ... See full document

... Many researchers have shown that a mechanism of grouping nodes, called clustering, which is performed dynamically, has a capacity to solve the scalability and energy efficiency problems in WSN. Clustering is an algorithm ... See full document

... In the dataset, the part of features is important to influence the study results, whereas the few features may not affect. Therefore, the features can be deleted to reduce the experimental cost and the result information ... See full document

... visited position for the particle is p ibest  ( p i 1 , p i 2 ,....... p id ) and also the best position explored. The best value so far is global best i.e., p gbest  ( p g 1 , p g 2 ,....... p gd ... See full document

... [8], particle swarm optimization (PSO) [9], biogeography-based optimization [10],intelligent water drop algorithm[11] ,harmony search[12] ,gravitational search algorithm[13],firefly ... See full document