Genetic Algorithm Based Clustering Data Mining And Application In Sale System

With the development of the information technology,the economical and social value of information resource is more and more important. In order for decision,it is the hard work that the valuable information or knowledge is discovered from numerous data. We need discover the interesting knowledge from the data warehouse. This knowledge is useful,but it cannot been predict. Because the method of Data Mining is put on,the people can realize the real value of data,which mean the information or the knowledge hide in data. Data Mining is one of the international advanced directions in the field of database and information decision.Data Mining has many research fields. The research of clustering algorithm is advanced. This dissertation is mainly on the theory and method of Data Mining and genetic algorithms based clustering algorithm. All the work can be concluded as follows:Firstly,induces the research work and development of Data Mining,including the Data Mining definition,the relationships with other academic fields,the imperative processes and its classifications. The principal techniques used in the Data Mining are surveyed also. The research of Data Mining and data warehouse relationship is the main work too. Data warehouse is the new saving data place for Data Mining,because it supportsdecision.Secondly,clustering is a promising application area for many fields including data mining,statistical data analysis,pattern recognition,image processing,etc. Many clustering algorithms have been developed. In this dissertation,on the base of clustering algorithm and genetic algorithms research,this dissertation optimized and improved the genetic algorithms,and presents an efficient algorithm. In the field of Data Mining research,genetic algorithm is a promising algorithm. The main challenge and key problem that clustering algorithm is applied to data mining is enormous data and to scan it,so efficiency is very important.Thirdly,build up the system prototype of data warehouse.Finish the system analysis,design and development,including the initiative design,detailed design and software design. This dissertation is under the environment of DG-CIMS including Order subsystem,Consign subsystem,price subsystem,and funds subsystem mainly. The system that has been developed is running successfully for 10 months.Lastly,the new algorithm gives some experimental results in DG-CIMS. On the base of the Data Mining and genetic algorithm based clustering algorithm research,the improved algorithm verifies the performance in DG-CIMS.