Investigation On Data Mining Techniques For Test-driving Database Of WS9 Aero-Engines

Data mining is a new research topic in database system research fields, and which can extract valuable information from large datas to help decision. In this paper, data mining techniques were introduced to investigate the test-driving database of WS9 aero-engines. The basic concept and general knowledge of data mining were given firstly, and the characteristics and research methods of data mining procedure were explained based on the test-driving database of WS9 aero-engines. Rough set and decision tree, these two classification mining methods were used to extract decision rules, regression analysis was utilized to find the relationship between variables, and the tendency also was predicted. Data mining implementation procedure for WS9 aero-engine test-driving database were accomplished by using rough set algorithm and decision tree algorithm under the VC++ 6.0 environment. The rules obtained from the data mining procedure were correct and can be used in accurate classification of the test-driving, and they provide valuable information for the experts. The results show that data mining techniques have an extensive application prospect and it is feasible to employ data mining techniques for analyzing aero-engines test-driving database.