The paper puts forward a data mining framework which is founded on temporal database, and realized a temporal data mining system in retailing based on the framework.

Currently,the common data model of the spatial-temporal data mining has the strong application directive property and low general applied capability.

As the spatial-temporal data increasing cosmically and data mining theories developing continuously, spatial-temporal data mining has become a research hotspot of experts and scholars in fields of computer and geography information system.

To overcome the demerits of traditional trend sequences analysis in temporal data mining,two concepts that were number trend sequences and trend sequences unwrapping were put forward.

To overcome the defects of data representation algorithms in temporal data mining,segmentation algorithm of key-point-based error checking is proposed.

A new time series data mining system based on Gray Regression Fuzzy Neural Network hybrid model is proposed in this paper and the establishing process of this hybrid model was mainly discussed.

Time series data mining is of great importance to development of society, sci.

Focusing on the disadvantages of the current ball mill pulverizing system optimization approa- ches,a ball mill pulverizing system optimization algorithm based on fuzzy time series data mining is pro- posed.

Research on Business Data Analyzing Method Based on Empirical Mode Decomposition and Dynamic Data Mining;

Based on properties of low temperature iron plating,use of dynamic data mining in quality control is described.

A new approach to solve the problem of dynamic data mining is presented.

Improvement in second cooling control of slab continuous casting by data mining technology;

Application of data mining in upgrading of CC process control system;

The application of data mining technology on flexible PVC formulation experimental research;