A Particle Swarm Optimization Algorithm for Storage Environments

摘要：

In order to guarantee safety, which need storage environment humidity, strictly control the temperature inside and outside factors. The PSO-BP neural network technology was applied to the control system of grain situation, the different positions of the granary of temperature and humidity, which provide data fusion processing parameters to improve the accuracy of measurement and goals. First, the BP neural network to initial data fusion of food, and then the PSO to the fusion results of particles. This new algorithm has coordinated contradictions between learning efficiency and convergence rate, and improved skilled speed and convergence rate. From the results of experiment, the new algorithm has some advantages, such as quickly, validity and practicability.

关键词： Particle Swarm Optimization BP algorithm expert system measurement and control for grain storage

作者: Bao Zhan Biao Wu Jianjun

作者单位: Henan University of Economics and Law Zhengzhou, China Henan University of Technology,Zhengzhou, China

会议类型: 国际会议

会议名称: 2010 International Conference on Circuit and Signal Processing(2010年电路与信号处理国际会议 ICCSP 2010)

会议地点: 上海

会议语种:英文

页码: 580-583

在线出版日期: 2010-12-25（万方平台首次上网日期，不代表论文的发表时间）