Rough-Set Theory in Solving Road Pavement Management Problems (Case Study: Ahwaz-Shush Highway)

Rough-Set theory as a mathematical tool for data mining, verifies the relationship among various factors and determines the shortest decision algorithm. In this study, the ability of the Rough-Set theory in the pavement management system has been evaluated with an empirical study using the collected data by the Ministry of Road and Urban Pavement Engineering on the Ahvaz-Shush highway (Southwest of Iran). The results of the Rough-Set theory procedure has been compared with other methods such as the artificial neural networks which is based on the data mining and regression method which is based on the mathematical correlation equations and AASHTO 93 method that is based on the deflection’s data. The results of this study confirm the stronger performance of the Rough-Set theory for determining the best decision algorithm in comparison with the other applied methods. The amount of data needed for modeling the problem would be decreased using the Rough-Set method and the efficiency of processing can significantly be increased

کلیدواژه ها:

Rough-Set Theory (RST) ، Decision making ، Pavement management system ، Neural network ، Regression method