Support vector data description with kernel density estimation (SVDD-KDE) control chart for network intrusion monitoring.

Multivariate control charts have been applied in many sectors. One of the sectors that employ this method is network intrusion detection. However, the issue arises when the conventional control chart faces difficulty monitoring the network-traffic data that do not follow a normal distribution as required.

Comparing the performance of Kernel PCA Mix Chart with PCA Mix Chart for monitoring mixed quality characteristics.

Along with the development of information and technology, the quality characteristics of a product cannot be monitored separately in the different types of control charts. In the past, conventional control charts were developed to monitor only one type of quality characteristic. The variable control charts are used to observe the variable or metric quality characteristics.

Kernel principal component analysis (PCA) control chart for monitoring mixed non-linear variable and attribute quality characteristics.

The products are commonly measured by two types of quality characteristics. The variable characteristics measure the numerical scale. Meanwhile, the attribute characteristics measure the categorical data.