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...

This paper presents an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Improved Particle Swarm Optimization (IPSO). In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. An iterative method is introduced to fin...

Clustering is a method which divides data objects into groups based on the information found in data that describes the objects and relationships among them. There are a variety of algorithms have been developed in recent years for solving problems of data clustering. Data clustering algorithms can be either hierarchical or partitioned. Most promising among them are K-means algorithm which is p...

The purpose of load frequency control is to reduce transient oscillation frequencies than its nominal valueand achieve zero steady-state error for it.A common technique used in real applications is to use theproportional integral controller (PI). But this controller has a longer settling time and a lot of Extramutation in output response of system so it required that the parameters be adjusted ...

in this paper, the gain in ld-celp speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (pso) algorithms to optimize the structure and parameters of neural networks. elman, multi-layer perceptron (mlp) and fuzzy artmap are the candidate neural models. the optimized number of nodes in the first and second hidden layers of el...

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

Inspired by the migratory behavior in the nature, a novel particle swarm optimization algorithm based on particle migration (MPSO) is proposed in this work. In this new algorithm, the population is randomly partitioned into several sub-swarms, each of which is made to evolve based on particle swarm optimization with time varying inertia weight and acceleration coefficients (LPSO-TVAC). At perio...

In order to improve the convergence speed and the drawback of easily converging to the local optimum of the standard particle swarm optimization (PSO), two improved PSO algorithms are presented based on the simple particle swarm optimization algorithm without speed attribute. One is introducing differential mutation technology of differential evolution algorithm into the simple PSO algorithm fo...

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...

Optimal design of large-scale structures is a rather difficult task and the computational efficiency of the currently available methods needs to be improved. In view of this, the paper presents a modified Charged System Search (CSS) algorithm. The new methodology is based on the combination of CSS and Particle Swarm Optimizer. In addition, in order to improve optimization search, the sequence o...