MPC strategy integrated with particle swarm optimization
Particle Swarm Optimization with Family Communication Strategy
... Abstract- Particle swarm optimization (PSO) is a population- based stochastic algorithm for solving complex optimization problems. To raise efficiency and accelerate convergence of PSO, we ...
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Individual Parameter Selection Strategy for Particle Swarm Optimization
... Zeng, 2004). There are still many other modified methods, such as fast PSO (Cui et al., 2006a), predicted PSO (Cui et al.,2006b), etc. The details of these algorithms can be found in corresponding references. The PSO ...
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A. Particle Swarm Optimization
... the particle goes through three hundred times iterations in each ...the particle enough opportunities to find a better ...our strategy improves the original PSO search results within the same number ...
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Complex stock trading strategy based on particle swarm optimization
... trading strategy whose weight vector was optimized by Particle Swarm Optimization ...trading strategy with a static choice of component weights is hard to perform well consistently over ...
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Enhanced Particle Swarm Optimization Algorithms With Robust Learning Strategy For Global Optimization
... Global optimization is a fast growing and significant research field, considering that it plays important role in various practical application fields such as business, science, engineering, finance, and many ...
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A Particle Swarm Optimization with Adaptive Multi-Swarm Strategy for Capacitated Vehicle Routing Problem
... the particle numbers for each ...the swarm groups for the current convergence ...increases/decreases particle number of the swarm ...makes swarm groups compete with each other, which is ...
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A Particle Swarm Optimization with Adaptive Multi-Swarm Strategy for Capacitated Vehicle Routing Problem
... the particle number changes is illustrated on Figure ...total particle numbers, which means the search performance is much better than PSOPC (GroupB) and PSO-RTVIWAC ...the particle number of QPSO is ...
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Darwinian particle swarm optimization
... with optimization algorithms is that of becoming trapped in a local ...a strategy based on natural selection in which, when a search tends to a local optimum, the search in that area is simply discarded and ...
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Adaptive particle swarm optimization
... Adaptive Particle Swarm Optimization Zhi-Hui Zhan, Student Member, IEEE, Jun Zhang, Senior Member, IEEE, Yun Li, Member, IEEE, and Henry Shu-Hung Chung, Senior Member, IEEE Abstract—An adaptive ...
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Particle Swarm Optimization with CUDA
... Through this platform, programmers can develop programs using common languages, especially Visual C++, for parallelization and execution of complex algorithms. In programming in the CUDA platform, a programmer needs to ...
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Application of Particle Swarm Optimization in Gain Tuning of Integrated Flight and Propulsion Control
... results obtained from the Genetic Algorith m (GA) in order to confirm the effectiveness of the proposed approach in optimization of IFPC gain tuning problem. The structure of simp le GA used in this paper is ...
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Particle filter with swarm move for optimization
... The particle swarm move in PSO algorithm is treated as the system dynamic in the state space model, while the objective function in optimization problem is designed as the observation ...model. ...
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A Gradient Multiobjective Particle Swarm Optimization
... where, h is the step size, a j (t) and ā j (t) are the jth archive variables before and after the MOG algorithm has been used at time t and the fitness values are updated at the same time. Moreover, the archive A(t) can ...
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Orthogonal learning particle swarm optimization
... Variant PSO algorithms, as detailed in Table IV, are used for comparisons. The parameter configurations are all based on the suggestions in the corresponding references. The first two are traditional PSOs of GPSO [23] ...
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Feedback learning particle swarm optimization
... In this paper, a feedback learning PSO with quadratic inertia weight has been proposed to solve various types of optimization problems. In the proposed PSO, the fitness information is used to control the ...
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A Modified Particle Swarm Optimization Algorithm
... every particle chooses its inertial factor according to the approaching degree between the fitness of itself and the optimal ...A particle with better fitness chooses a smaller inertial factor and a ...
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A Hardware Architecture of Particle Swarm Optimization
... Multi-Swarm Strategy (MSPSO) is introduced to solve this ...Multi-Swarm Strategy, particle swarm is divided into several groups, and each group exploits different kinds of PSO ...
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Empirical Study of Segment Particle Swarm Optimization and Particle Swarm Optimization Algorithms
... decades, optimization algorithms with mathematical programing have proved to be effective in solving large complex optimization ...Recently, swarm intelligence techniques have gained popularity ...
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Particle swarm optimization application in optimization
... A multilayer perceptron model of beltline moulding was used to determine the optimal number of hidden units to represent the model and particle swarm optimization was used to min[r] ...
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3 Particle Swarm Optimization
... Keywords PSO; neural network; time series; air pollution prediction; SPM. Mathematics Subject Classification 68T20, 65K10. 1 Introduction In recent years neural network modeling has been an interesting open problem and ...
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