›› 2017, Vol. 30 ›› Issue (4): 56-.

• 论文 • 上一篇    下一篇

基于群智能算法的神经网络建模研究

王闪闪   

  1. (上海理工大学 光电信息与计算机工程学院,上海200093)
  • 出版日期:2017-04-15 发布日期:2017-04-11
  • 作者简介:王闪闪(1990-),女 ,硕士研究生。研究方向:神经网络。

Research of Neural Network Model Based on Swarm Intelligence Algorithm

WANG Shanshan   

  1. (School of Optical-Electrical Information and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
  • Online:2017-04-15 Published:2017-04-11

摘要:

针对神经网络建模过程中不合理的权值选取,使训练陷入局部最优解而得不到全局最优解这一问题。采用群智能算法得出全局最优解,并且利用检验样本达到最低点时的权值与阈值正确建立神经网络模型。结果表明,网络模型的评价参数表现良好,其中预测精度与相关系数分别为97.55%和96.2%。从而证明了基于群智能算法的神经网络,在遵循建模条件情况下能够保证取得全局最优解,建立的模型性能良好,具有一定的理论与市场应用价值。

关键词: 神经网络, 群智能算法, 全局最优解, 优异性能

Abstract:

It is not reasonable to select the appropriate weights to bring out the desired results with the global optimal solution on the misleading of local optimal solution in the process of neural network model.A swarm intelligence algorithm is used to obtain the global optimal solution and the neural network model is established by using the weight and threshold value of the sample to the lowest point. The results showed that the evaluation parameters of the network model showed good performance, the prediction accuracy and the correlation coefficient were 97.55% and 96.2% respectively among them. Examples show that the neural network based on swarm intelligence algorithm can be able to get the global optimal solution and the model has good performance under the modeling condition which can prove its great value in theory and market.

Key words: neural network, swarm intelligence algorithm, global optimal, modeling conditions

中图分类号: 

  • TP183