Abstract: In order to explore the relational characteristics between and within the attributes of HVB, a coupling association analysis model of HVB should be built. Firstly, distribution characteristics and association relationships of the violation attribute values were analyzed. The correlation coefficients of the corresponding attributes under various violations were obtained by using the ARM and coupling relation theory. A set of coupling correlation degree vectors, meanwhile, was obtained,and the vectors were ranked from large to small. And then, according to the sorted coupling correlation degree vector set, the coupling association analysis model of HVB was mapped. In the end, 3 indicators, recall rate, precision rate and mean absolute error (MAE) were introduced to solve the indicators results of the data set and the model. A comparison was made between the model and ARM analysis results.The result shows that the model performs well in accuracy and comprehensiveness for habitual violation behavior's association relationship analysis.

Key words: habitual violations, association rules management (ARM) thought, coupling relation, analysis of relational characteristics, coupling association analysis model