The blending process of raw coal‘s being sold to power plants is a optimization process of pursuing the cost minimization under certain constraints. Among all intelligent algorithms solving those kinds of optimization problems, Particle swarm optimization (PSO) algorithm is relatively a better choice. This paper describes the improvement of the PSO by turning single-objective optimization probl...

Particle Swarm Optimization (PSO) is one of the most powerful algorithms for optimization. Traditional PSO algorithm tends to suffer from slow convergence and trapping into local optimum. In this paper, an improved PSO algorithm is proposed by combining dynamic fractional order technology and the wavelet mutation strategy. In the proposed method, a dynamic fractional order velocity update equat...

Particle swarm optimization(PSO) has been applied on feature selection with many improved results. Traditional PSO methods have some drawbacks when dealing with binary space, which may have negative effects on the selection result. In this paper, an algorithm based on fitness proportionate selection binary particle swarm optimization(FPSBPSO) will be discussed in detail aiming to overcome the p...

This paper presents a novel dynamic neural network (DNN) predictive control strategy based on modified particle swarm optimization (PSO) for long time delay nonlinear process. The proposed dynamic NN structure could approximate to the actual system model and obtain the pure delay time exactly. An improved version of the original PSO is put forward to train the parameters of NN to enhance the co...

Recently, Particle Swarm Optimization (PSO) has evolved as a promising alternative to the standard backpropagation (BP) algorithm for training Artificial Neural Networks (ANNs). PSO is advantageous due to its high search power, fast convergence rate and capability of providing global optimal solution. In this paper, the authors explore the improvements in forecasting accuracies of feedforward a...

With an ever-growing attention Particle Swarm Optimization (PSO) has found many application areas for many challenging optimization problems. It is, however, a known fact that PSO has a severe drawback in the update of its global best (gbest) particle, which has a crucial role of guiding the rest of the swarm. In this paper, we propose two efficient solutions to remedy this problem using a stoc...

This paper studies the defect detection problem of adhesive layer of thermal insulation materials. A novel detection method based on an improved particle swarm optimization (PSO) algorithm of Electrical Capacitance Tomography (ECT) is presented. Firstly, a least squares support vector machine is applied for data processing of measured capacitance values. Then, the improved PSO algorithm is prop...