提出一种基于支持向量数据描述(support vector data description,SVDD)的生产过程监控、诊断与优化方法.首先,利用正常样本建立SVDD监控模型,获得控制限;然后,利用贡献图对超过控制限的异常点进行诊断,分析引起异常的主要原因;最后,利用邻近点替换法对异常的生产样本进行工艺参数优化.将新方法应用于热轧薄板的生产过程中,结果表明:新方法比传统的监控方法T2 PCA具有更高的检出率,且可以实现对异常点的工艺参数优化,使之回到受控状态
4.1 Conflicts of the traffic at an intersection 4.2 Traffic Signals 4.3 Traffic Controller 4.4 Installation of traffic signals at intersection 4.5 Functions of Monitoring System 4.6 Traffic Detection and Data Processing 4.7 Traffic Detection Equipment 4.8 Environment detection 4.9 System Structure of Monitoring Center
Chapter 1 Recent Advances in Pattern Classification Chapter 2 Neural Networks for Handwriting Recognition Chapter 3 Moving Object Detection from Mobile Platforms Using Stereo Data Registration Chapter 4 Pattern Classifications in Cognitive Informatics Chapter 5 Optimal Differential Filter on Hexagonal Lattice Chapter 6 Graph Image Language Techniques Supporting Advanced Classification and Cognitive Interpretation of CT Coronary Vessel Visualizations Chapter 7 A Graph Matching Approach to Symmetry Detection and Analysis
