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    When dealing with supervised recursive neural networks, this article describes the BPTS training algorithm as well as its improved algorithms and the best PSO algorithm in training forward neural network is also used to train recursive neural networks.
    To improve further the performance of PSO(Particle Swarm Optimization), a modified PSO algorithm is proposed and called CSV-PSO algorithm. Based on the best fitness of the particles, the ranges of both search space and velocity of the particles are contracted dynamically with the evolution of particle swarm in CSV-PSO algorithm.
    为了改善粒子群优化(PSO)算法的搜索性能,提出一种改进的粒子群算法CSV PSO算法·该算法在粒子群进化的过程中根据粒子群的最佳适应值动态地压缩粒子群的搜索空间与粒子群飞行速度范围;
    Simulation study results on fresh temperature in power plants, which is characterized by parameter uncertainty, liable to disturbances and time-lay, show that PSO algorithm is distinguished by its ability of quick searching and of reducing calculation work required, thus providing a very efficient way of optimizing the parameters of fuzzy controllers, and herewith markedly imroving control quality of the fresh steam temperature control system under all loading conditions.
    This article mainly introduces the advantage of PSO algorithm compared with Genetic Algorithm (GA) system by the experiments.
    Then taking the Toyota's mixed-model scheduling function as the target function,the adapted discrete PSO algorithm is used to solve that problem,and the satisfactory feasible solutions are achieved.
    Finally,we give numerical examples and the performance analyses of the algorithm. Comparing with the genetic algorithm,we show that the PSO algorithm is effective and practical for solving Nash equilibrium.
    This paper offers an Adaptive PSO Algorithm. A fuzzy system is implemented to dynamically adapt the inertia weight of the PSO,here two variables are selected as inputs to the fuzzy system (the current best performance evaluation and the current inertia weight),the output variable is the change of inertia weight.
    Base on the target frequency characteristics,we establish the optimization model and solve it by high speed PSO algorithm.
    Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA-based algorithms in searching for the best solution to the DM problem.
    This paper introduces a conceptual overview and detailed explanation of the PSO algorithm, as well as how it can be used for antenna array design, and presents several results optimized by PSO, which show the abroad application foreground of PSO in the antenna array design.
    In this paper,we have presented a new PSO algorithm,improved velocity mutation particle swarm optimizer(iPSOVMO).
    In order to improve its performance,the paper puts forward a hybrid algorithm which blends the PSO algorithm and simulated annealing algorithm.
    Numerical results for the forward position analysis of in-parallel manipulators show that the PSO algorithm possesses the performances of rather quick convergence speed and high precision.
    First, The standard RBF network is introduced and analyzed in this paper. Then the Particle swarm optimization algorithm is introduced and a RBF neural network based on PSO algorithm is proposed to optimize the network parameters. Finally the PSO- RBF network is applied to Coiling Temperature Control (CTC) to predict coiling temperature.
    An example shows that,the method effectively releases the difficulty of former PSO algorithm in finding the feasible solution of optimization problem.
    The numerical results of detecting damages at one or multiple sites for a two-storey rigid frame and the convergence curves of PSO algorithms show that the proposed improved PSO algorithm is more effective to solve the constrained optimization problem than the traditional PSO algorithm with an inertia factor.
    The vast number of experiment results show that the new swarm intelligence algorithm has much stronger global searchingability compared to the classical PSO algorithm.
    We solve the upper model by PSO algorithm and lower model by the non-equilibri- urn logit traffic assignment algorithm based on paths generated by the shortest path algorithm.
    A simplified off-lattice model of protein is studied with a PSO algorithm. Interaction between atoms is represented by a physical-based potential.
    The design results indicate the improved PSO algorithm is simple and easy to implement,needs fewer adjustment parameters,guarantees global convergence and rapid search for quality optimal solutions,thus producing good effects for the reliability optimal design of the laminated structure of composite materials.


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