山东理工大学学报：自然科学版2011，Vol.25Issue(6)：29-33,5.
改进的BP神经网络及其在销量预测中的应用
Sales forecasting model based on improved BP neural network
毕建涛 1魏红芹1
作者信息
- 1. 东华大学旭日工商管理学院,上海200051
- 折叠
摘要
Abstract
In the light of different factors affecting sales of products and the interaction between those factors,the theory of artificial neural network was introduced into the domain of sales forecasting.At the same time,BP neural netowrk was improved both from the aspects of sample data quality and initial parameters to overcome its limitation by combining principal components analysis（PCA）,BP neural network and particle swarm optimization algorithm（PSO）.Finally,an example analysis was made in order to verify the validation of this model.The results showed that the suggested model simplified the architecture of BP network and improved forecast accuracy.Thereby,the effectiveness of this model was validated.关键词
销量预测/主成分分析法/BP神经网络/粒子群优化算法Key words
sales forecasting/principal components analysis（PCA）/back propagation neural network/particle swarm optimization algorithm（PSO）分类
信息技术与安全科学引用本文复制引用
毕建涛,魏红芹..改进的BP神经网络及其在销量预测中的应用[J].山东理工大学学报：自然科学版,2011,25(6):29-33,5.
