In order to improve the prediction ability of the Neuron Network in stock index prediction, we proposed an improve particle swarm neural network algorithm. The Particle Swarm Optimization algorithm based on Parasitic Immune (PSOPI) was used to optimize combination weights of BP neural network model parameters. The BP algorithm was also to obtain the parameters of network further accurate. Final...

Partner selection is a critical issue in the research of virtual enterprise. It is usually a combinatorial optimization problem. In this paper, an improved discrete particle swarm algorithm is proposed for the partner selection optimization. At first, an optimization model is presented, which includes the main crucial factors for partner selection, such as running cost, reaction time and failur...

With the target of achieving dense storage of packed medicine of rapid dispensing system in automated pharmacy, an improved adaptive chaotic particle swarm optimization (IACPSO) algorithm was proposed to solve the storage planning problem. According to the proposed IACPSO algorithm, the diversity of the particle swarm was enhanced by using the ergodicity of the chaos motion to initialize the sw...

Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was...

Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. An efficient algorithm must have symmetry information between participating entities. Enhancing efficiency relative the symmetric concept is a critical challenge in field security. PSO also becomes trapped into local optima similarly other nature-inspired algorithms. The literature depicts th...

The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...

In order to design and optimize high-linearity power amplifier (PA), which with nonlinear and memory effect, it is very important to build power amplifier behavior modeling accurately. This paper proposes a power amplifier behavior modeling based on RBF neural network with improved chaos particle swarm optimization algorithm. To make the particles evenly distribute in the problem search space, ...