Design and Implementation of Data Mining System Based on Traditional Chinese Medicine Extracted
基于中药提取的数据挖掘系统设计与实现①

Data mining methods are applied to the system to extract data for analysis of Chinese medicine and forecasting. First, the data integration and discrete treatment are made, to obtain appropriate data mining data sets. Then k-means and DBSCAN clustering algorithm are used to cluster the data quality control. Quality control process parameters interval are obtained. Apriori algorithm is improved by adding a user interest degree in the concept. The candidate set of exponential growth is controlled. The relationship between parameters and solids is got. By using three-layer BP neural network algorithm trained network model, the relationship between the process parameters and results quality parameters is obtained. The law implied in the data is found. It provides a scientific analysis and decision support for enterprises to optimize processes and improve their productivity and reduce the costs.