Study Andapplication Of Data Mining In Project Cost Data Management System

With the construction project cost data management systems being used, theproject cost data is accumulated in the database. The staffs of project cost datamanagement for the general operation is query operations and simple statisticaloperations. Because of a lack of deep analysis of the cost data, it is difficult to findthe intrinsic factors that affect the cost data fluctuations. There are many intrinsicfactors that affect the cost data fluctuations,but the valuable information can not beobtained as to utilizing general methods.The relevant rules that the project cost dataincludes can be found through the relevant theories and techniques of data mining,we can understand the reasons of affecting the project cost data’s fluctuation, thus itprovides some references for the building industry practitioners to certain aspectssuch as controlling project costs and improving the quality of project management.This thesis mainly dissertates the theory of data mining and the application ofthe decision tree technology in the construction project cost data management andsystem.The thesis mainly dissertates several aspects: Firstly, information technologyand data mining developments in construction project cost data management wereintroduced, and the issues of management the project cost data is introduced; then itintroduces the concept of data mining and data mining steps, while common datamining algorithms are briefly introduced,and it tells the specific application of datamining in the relevant industries; then the basic steps and evaluation criteria for theclassification algorithm are briefly stated,while the thesis introduces features andimplement steps of several common the decision tree algorithms ID3algorithm, C4.5algorithm and CART algorithm;after that the thesis introduces the constructionproject cost data management system’s overall structure and logical structure,thengive a solution about decision tree technique application: identifying data miningobjects and collection of study object, and data preprocessing, while taking advantageof C4.5decision tree algorithm to obtain the decision tree model and classificationrules. Finally, the thesis makes overall summarization, and expects the data mining inthe application of the construction project cost data management system.