网上购物系统的设计与开发

网上购物系统具有强大的交互功能,它的主要特点就是改变了购物只有到现实商场的惯常做法,这种全新的交易方式采用Web技术,借助于Internet互联网广泛应用,达到资源共享,实现公司间文档与资金的无纸化交换,并使商家和用户方便地传递信息,完成电子贸易或EDI交易。

Time-varying Process Outlier Detection Based on Reinforced Sparse PCA

In order to improve the traditional outlier detection technology to adapt to the time-varying characteristics caused by equipment aging and catalyst failure in industrial process，the reinforcement learning is used to explore the Tennessee Eastman industrial environment to extract the optimal characteristic variables. The sparse PCA algorithm is applied for outlier detection according to the ex? tracted variables and the results are compared with reinforced PCA，sparse PCA and KNN models. The experimental results show that the RSPCA model can effectively extract the optimal modeling variables and establish an optimal outlier detection model with an accuracy of 93.33%. The feature extraction method based on reinforcement learning can effectively reduce the dimensionality of high-dimensional data. The outlier detection based on sparse PCA improves the recognition rate of outliers and enhances the interpretation ability of principal components.