| Title |
The Development of a Productivity Prediction System in the Structural Framework of Apartment Housing Projects Using Data Mining Technique |
| Authors |
Woo Gi-Beom ; Oh Se-Wook ; Kim Young-Suk ; Kim Yea-Sang |
| Keywords |
Productivity ; Apartment Housing ; Productivity Prediction ; Data Mining ; Multiple Regression Analysis |
| Abstract |
Productivity data plays an important role in planning and managing a construction project. It is due to the fact that the productivity data is closely related to planning, monitoring, and controlling the major construction information such as time, cost and quality of a project. Recently, there have been several researches for collecting, analyzing, and accumulating productivity data using information technology such as PDA, barcode, RFID, and data warehouse in the construction industry. However, there are few researches that suggest how to systematically utilize construction productivity data accumulated in database as reference in planning and construction phases of the project. The primary objective of this research is to propose a computerized system for predicting construction productivity data in planning and construction phases of the structural frame work of apartment housing using data mining technique. Authors expect that the effective use of the proposed system would significantly improve the objectivity of project baseline and the reliability of project performance evaluation result, and help construction managers systematically manage and accumulate useful construction productivity data that would be utilized as a reference in future construction projects. |