Data Mining And Its Application In Process Industry

In recent years, Data Mining becomes increasingly important and has widely applied in process industry, mainly for two reasons. On one hand, data mining technique is developing very quickly. Due to the development of data acquisition and database technique, a huge stock of data are accumulated in human's activities, therefore, a powerful analysis tool is needed to deal with the data. Data mining is the solution for this problem and has found its applications in various areas such as business, engineering technology and scientific study. On the other hand, the phenomenon that the information system has greatly facilitated the process industry and the equipment of process check and process control widely applied in the process industry has created a favorable environment to apply data mining to the process industry. However there still exist many allication problems because of the complexity of process data.In this thesis, data mining technology based on rough sets for triazophos synthesis process is discussed as follows:Firstly, the production data of the triazophos synthesis process are preprocessed because there are many noisy, missing, and lagged data in the process industry. Condense the data and reduce them to a proper numbert. A nonlinear regression based on the method of least squares is estimated and polyfit the data in a window, thus eliminate the noisy and missing data, adjust the time series data, eliminate the time delay and get the accurate result. And finally a global supervisory discretization based on data distributed character is proposed to turn numeric attributes into discrete ones.The discrete data are mined by the arithmetic based on rough set theory. Firstly a global decision system is established and estimated and then divided into two parts: one is a consistency system and the other a non-consistency system. For the consistency system an algorithm for acquisition of decision rules to the decision attributes is proposed;for the non-consistency, the decision rules are got directly. Finally, the solution for the discrete data is obtained.This solution has been proved to be effective in a triazophos plant.