Study And Application Of Correlation Analysis Methods In Anomaly Detection

This thesis mainly focuses on that the correlation analysis method is applied in anomaly detection, and this method is used in feature selection and earthquake feature data's anomaly detection. At the same time, the prototype software system of using data mining theory and technology to forecast and judge earthquake tendency was developed. The main contents are as follows:This thesis proposes a new method of Feature Subset Selection, which is based on discrete Binary version of Particle Swarm Optimization (BPSO) and Overlap Information Entropy (OIE). This method does not depend on classifier. The main idea is: at first, a group of particles are generated randomly. The OIE between attribute set and class attribute is used as BPSO algorithm's fitness function, its size denotes the correlation degree between selected attribute set and class attribute. Then, feature subset is optimized by BPSO. Finally, feature subset, which has the largest OIE with class attribute, is selected as the Optimal Feature Subset. Experimental results confirm that this method can not only find the Optimal Feature Subset effectively but also do feature reduction and remove the redundant information, and its classification results are not worse than all features'classification results.The concept of A New Nonlinear Correlation Information Entropy (NNCIE) is proposed based on the study of Correlation Information Entropy (CIE) and Hpal Entropy. Under the condition of the largest partition of finite sets, some properties of this information entropy are derived and proved theoretically and these properties meet the basic properties of the information entropy, which is proposed by Shannon C E. The NNCIE is a measurement criterion of multi-variable and nonlinear system's correlation degree. As an uncertainty measurement of multi-variable correlation, the more correlation information between variables contain, the smaller value of corresponding NNCIE is. The NNCIE contributes to information fusion and provides a new method and idea for the research of correlation analysis theory. The results of NNCIE show that NNCIE is an effective and useful measurement method for nonlinear system's uncertainty.Based on above research results, the software prototype system of using data mining theory and technology for prediction and judgment earthquake tendency was developed. But this system is not an application software system, and its development just only supplies a good foundation for subsequent research. Correlation analysis module is one of main constituent part, and this module makes the NNCIE be the fitness function of feature selection method that this thesis proposed. At the same time, a visual operation interface is provided for user and its main function is feature selection and anomaly detection so as to judge this feature selection method's availability. Experimental data is WenChuan aftershock's feature data, and the test results show that the software runs well.