Wavelet neural network (WNN) is a combination of wavelet analysis and neural network and has the strong fault tolerance, the strong anti-jamming and the strong adaptive ability. However, WNN is likely to trap local minimum and premature convergence. According to these shortcomings, particle swarm optimization (PSO) algorithm is applied to wavelet neural network (WNN) and has good effect. This p...

In this paper, optimal placement of Phasor Measurement Unit (PMU) using Global Positioning System (GPS) is discussed. Ant Colony Optimization (ACO), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for this problem. Pheromone evaporation coefficient and the probability of moving from state x to state y by ant are introduced into the ACO. The modifi...

In this article the hybrid optimization algorithm of differential evolution and particle swarm is introduced for designing the fuzzy rule base of a fuzzy controller. For a specific number of rules, a hybrid algorithm for optimizing all open parameters was used to reach maximum accuracy in training. The considered hybrid computational approach includes: opposition-based differential evolution al...

Particle Swarm Optimization is an algorithm capable of optimizing a non-linear and multidimensional problem which usually reaches good solutions efficiently while requiring minimal parameterization. The algorithm and its concept of “Particle Swarm Optimization”(PSO) were introduced by James Kennedy and Russel Ebhart in 1995 [4]. However, its origins go further backwards since the basic principl...

Differential Global Positioning System (DGPS) provides differential corrections for a GPS receiver in order to improve the navigation solution accuracy. DGPS position signals are accurate, but very slow updates. Improving DGPS corrections prediction accuracy has received considerable attention in past decades. In this research work, the Neural Network (NN) based on the Gaussian Radial Basis Fun...

clustering is a widespread data analysis and data mining technique in many fields of study such as engineering, medicine, biology and the like. the aim of clustering is to collect data points. in this paper, a cultural algorithm (ca) is presented to optimize partition with n objects into k clusters. the ca is one of the effective methods for searching into the problem space in order to find a n...

Highly multimodal function optimization is similar to many other optimization problems requiring many iterations and large number of function evaluations. Glowworm Swarm Optimization (GSO) is one of the common swarm intelligence algorithms, where GSO has the ability to optimize multimodal functions efficiently. Locating the peaks of a high-dimensional multimodal function requires a large popula...

one of the most important applications of multi-objective optimization is adjusting parameters ofpractical engineering problems in order to produce a more desirable outcome. in this paper, the decoupled sliding mode control technique (dsmc) is employed to stabilize an inverted pendulum which is a classic example of inherently unstable systems. furthermore, a new multi-objective particle swarm o...

Abstract A brushless DC (BLDC) motor is synchronous with trapezoidal/square wave counter-electromotive force, which a typical example of highly coupled nonlinear systems. In industrial control, BLDC drive usually uses proportional–integral (PI) controller to control the speed, but it very difficult adjust scale factors. this study, we present particle swarm algorithm-tuned fuzzy logic-PI (PF-PI...