一、引言结构化分析设计方法是一种较为成熟和完善的 MIS 开发方法,它直观易学,普遍流行,并有不少已实现的系统正在正常运行。尽管随着 MIS 的深入研究,结构化分析设计方法暴露了一些严重缺点,而提出一些新的 MIS 开发方法,如快速原型法和面向对象方法等,但结构化分析设计方法依旧保持着生命力,并且在新的开发方法中,往往被结合使用。
A new method by integrating the multivariate statistical analysis with neural network used for complex pattern classification was proposed in this paper. First, a particularly developed statistical method called correlational components analysis was employed to extract pattern characteristics from the original sample pattern space. These pattern characteristics were then used as inputs to a multi-layered feedforward neural networks for further pattern classification, The proposed approach transforms the complex patterns into lower dimensional and mutually decoupled ones, it also takes the advantages of the self-learning capability of the neural networks. Finally, a practical example of natural spearmint oil was used to verify the effectiveness of the new method. The results showed that the proposed integrated approach gives better results than other conventional methods.
