Making a Decision Between the Rehabilitation and Reconstruction of Asphalt Pavements Using the Rough-Set Theory

Every year a great amount of money is expended for the rehabilitation and reconstruction of roads and pavements in most countries. Besides, making an ideal decision on this based on the types of failures determined, takes too long. The rough-set theory is an e ective tool for the analysis of information systems in a Pavement Management System (PMS) database gained by both objective and subjective methods. A rough-set based analysis acts like a knowledge engineer who sits between data and the user. This approach appears to capture information on uncertainty, imprecision and ambiguity along with precise values in a PMS database. This paper explores a new approach to the rough-set theory in a PMS database that enables pavement engineers to discover the shortest subsets of condition attributes having quality equal to the general quality of de ned characteristics in the information system, to assess and describe pavement conditions, and to derive decision rules for rehabilitation and reconstruction of the pavements. To evaluate the results, the best algorithm of de ned attributes in the information system is determined by making use of a stepwise linear regression method and the result is compared with rough-set ones. The results of the research indicate that the rough-set theory has a better and stronger operational capability in identifying the e ective parameters for the severity evaluation of typical distresses in asphalt pavements and in decision-making for selecting the type of repair.