This article proposes an improved particle swarm optimization (PSO) with suggested parameter setting “Selective Particle Regeneration”. To evaluate its reliability and efficiency, this approach is applied to multimodal function optimizing tasks. 12 benchmark functions were tested, and results are compared with those of PSO and GA-PSO. It shows the proposed method is both robust and suitable for...

In optimizing the particle swarm optimization (PSO) that inevitable existence problem of prematurity and the local convergence, this paper base on this aspects is put forward a kind of modified particle swarm optimization algorithm, take the gradient descent method (BP algorithm) as a particle swarm operator embedded in particle swarm algorithm, and at the same time use to attenuation wall (Dam...

Dynamic structural responses via time history analysis are highly dependent to characteristics of selected records as the seismic excitation. Ground motion scaling is a well-known solution to reduce such a dependency and increase reliability to the dynamic results. The present work, formulate a twofold problem for optimal spectral matching and performing consequent sizing optimization based on ...

The paper proposed a network scheduling in cloud computing based on intelligence Particle Swarm Optimization algorithm aimed at the disadvantages of cloud computing network scheduling. Firstly, on the basis of cloud model, used intelligence Particle Swarm Optimization algorithm with strong ability of global searching to find the better solution of cloud computing network scheduling then turned ...

This paper presents the application of metaheuristic methods to the minimum crossing number problem for the first time. These algorithms including particle swarm optimization, improved ray optimization, colliding bodies optimization and enhanced colliding bodies optimization. For each method, a pseudo code is provided. The crossing number problem is NP-hard and has important applications in eng...

The particle swarm optimization algorithm (PSO) has two typical problems as in other adaptive evolutionary algorithms, which are based on swarm intelligence search. To deal with the problems of the slow convergence rate and the tendency to trap into premature, an improved particle swarm optimization with decline disturbance index (DDPSO) is presented in this paper. The index was added when the ...

The paper puts forward an unmanned aerial vehicle (UAV) fixed-point reconnaissance route planning method. The method introduces the improved particle swarm optimization (IPSO) method to the planning of UAV reconnaissance route and adds the objective value, effective reconnaissance route and other factors affecting UAV reconnaissance route in the objective function of particle swam to obtain the...

At the late evolution stage of the basic particle swarm optimization (BPSO), convergence process starts to slow down and the best fitness particle fluctuates around the globally-optimal solution, which may give rise to decrease on convergence precision of the BPSO. Therefore, an improved algorithm for particle swarm optimization was proposed. The modified version of PSO uses a controllable velo...

This paper presents an optimal design of linear phase digital low pass finite impulse response (FIR) filter using Novel Particle Swarm Optimization (NPSO). NPSO is an improved particle swarm optimization (PSO) that proposes a new definition for the velocity vector and swarm updating and hence the solution quality is improved. The inertia weight has been modified in the PSO to enhance its search...