Particle Swarm Optimization (PSO) algorithm is a new optimization approach, which has been widely used to solve various and complex optimization problems. However, there are still some imperfections, such as premature convergence and low accuracy. To address such defects, an improved PSO is proposed in this paper. The improved PSO algorithm introduces a uniform search strategy that makes partic...

With development of the computer technology, the large-scale calculation problems are often appeared in the network, it needs a lot of system resources and support of hardware, it often bring troubles in engineering optimization, so it needs apply the method such as the group's global optimization method and its improved algorithm to obtain reliable results in the computer system. In the study,...

Indoor localization algorithm has low precision and high cost. Based on the VIRE algorithm, this paper proposes a RFID technology based on particle swarm optimization algorithm. Firstly, the improved threshold of wavelet algorithm to the read signal for de-noising and reduce the signal strength value fluctuations generated error; and then the weighted localization to improve the positioning acc...

Particle swarm optimization algorithm in solving complex functions, such as slow convergence, accuracy is not high, easily falling into local optimum problem. Based on the chaos optimization is introduced into particle swarm optimization algorithm, given the chaotic particle swarm optimization algorithm. In order to improve the image quality of CMOS image sensor, the image of the main noise sou...

in this article, a multi-objective memetic algorithm (ma) for rule learning is proposed. prediction accuracy and interpretation are two measures that conflict with each other. in this approach, we consider accuracy and interpretation of rules sets. additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. this...