Application Research Of Data Ming Technology In Port Enterprise

Since the opening and reformation, Along with developing of China economy, The production scale of port enterprises in China is continually expanding. Import and export cargo amount is rapidly increasing. Port enterprises can't find the distribution data by sense under the law and under the laws of analysis in decision-making. Excavation data (Data Mining, DM) is a method and show the flow of new knowledge. Through analysis of specific data, we found that the definition of effective, innovative, potential value, the unknown, and ultimately understandable information for the enterprise sector to make good business decisions and important decision-making help.This thesis explained how to use association analysis and clustering analysis in port enterprises to realize Apriori excavation data algorithms for cargo and K-means excavation data algorithms for enterprise clients.First, the thesis discussed application forms and implementation steps of data mining algorithm in port enterprises, on the basis of presenting the data excavation definitions, workflow and its realization and technical analysis on the data tap algorithms.Secondly, it explore the data analysis method by using association analysis with a database classification aggregation technology with finding the association rule via analysis, it provide the administrative decision for port enterprises in cargo pile-up and transportation.Then, it discusses how to using K-means of clustering analysis to make analysis for the client of port enterprises. It providers the administrative decision for developing latency clients at the basis of classifying of clients of enterprises.Finally, design and realize a data mining system. And realize visual analysis. the thesis gave the main procedure code for common users.