Study on Project Decision Based on Data Mining of Rough Sets

In the paper, the procedure of construction project decision based on data mining of Rough Sets is discussed. This paper takes a construction project as a case study. The risk decision of construction project is sort of multiple attribute decision-making processes. It is certain that we have to deal with massive data. So data mining technology is necessary, for it can abstract implicit regularity from massive data. In this paper, the reduction algorithm based on Rough Sets is proposed as a practical data mining technology. In the paper, the procedure of construction project decision is analyzed. And a new decision method is proposed in order to solve the risk decision problem of a construction project. The factor set is established including condition attribute and decision attribute. Then experts qualitatively describe risk factors and create a decision table, and the attribute reduction algorithm based on Rough Sets is used to eliminate the redundant risk factor and its value of decision table. Finally, the minimum decision rules are created based on data mining results. And the rules with explain meanings are abstracted in the case study. We can make proper decision from the rules to improve precision and explanatory ability in practice.